TW201211509A - Navigation devices - Google Patents

Abstract

A method of creating map data including search acceleration data arranged to increase the speed at which a route can be planned across an electronic map comprising a plurality of navigable segments, each navigable segment representing a segment of a navigable route in the area covered by the map. wherein the method comprises: (a) reducing the number of navigable segments to be considered in the creation of the search acceleration data by removing navigable segments to form a core network of navigable segments; (b) dividing the electronic map into a set of hierarchical regions such that the or each navigable segment is categorized into at least one region in each level of the hierarchy: (c) using a time varying function associated with at least some, and generally each, navigable segment of the core network to determine whether that navigable segment is part of minimum cost route to at least one of the regions and recording this determination in the search acceleration data: and To be accompanied by Figure 7a when published

Description

201211509 VI. Description of the Invention: [Technical Field to Be Invented] The present invention relates to a computerized method and related system for generating map data. Specifically (but not exclusively) the method of generating map data is used to facilitate route planning between at least two points in accordance with a predetermined cost function. Embodiments of the present invention can generate search acceleration data that reduces the time it takes to generate a route when the search acceleration data is used for route planning. [Prior Art] A route planning device (often referred to as a satellite navigation portable navigation device (PND) or the like) along with a global information network (www) (such as httP://routes.tomt〇mc〇m/) The web site that is accessed is well known to us and allows its users to plan the route between the two points. This technique can be generally referred to as electronic route planning or route planning only. The map material used for this electronic route planning comes from a professional map supplier such as Teh. When performing this route planning on the PND, the location data from the GPS system is usually used. However, other applications allow the user to enter their location or other points to consider for the purpose of routing pianning. This map material contains a number of roads (and other navigable paths) that can be described as lines—that is, 'vectors or road segments (eg, starting point, end point, direction of the material, and the entire road in the raft is made up of hundreds of These segments are composed, and each k is determined by the start/end direction parameter only _ boundary ^). The map is the road vector, the data associated with each vector (speed limit, direction of travel, etc.) force /, interest point (Ρ〇Ι) plus road name plus other geographic features (such as parking lot 150831.doc 201211509 boundary a set of turbulent boundaries, etc., all bounded by a vector: two: t system corresponding or t-boundary & all map features associated with the G ρ s coordinate system (eg, road vector, P0I, etc.), thereby The location of the device as a heart via the GPS system can be placed on the relevant road displayed by the map order and allowed to plan to the destination best route. Θ This map material can be extensive. Some maps are known to cover areas with more than 120,000, _ vectors, and the map data is a map covering Europe and Russia. By the way, using this map material to plan a route is complex and time consuming. Again, this route is known to be a compromise between accuracy and time. > The prior art that has considered the idea of improving the speed at which path selection can be made includes US 6,636, _, which is discussed for a much smaller map size (such as the Western European Highway Network (which has approximately 4 〇) 〇, 向量 a vector)) Improvement of the A best priority search strategy. SUMMARY OF THE INVENTION According to a first aspect of the present invention, a method for generating a map body including search acceleration data is provided, the search acceleration data being added to an electronic map including a plurality of navigable segments. To plan the speed of a route, the parent-navigable segment represents one of the navigable routes in the area covered by the map, where the method comprises: a) by removing the navigable segment to form one of the navigable segments Networking to reduce the number of navigable segments to be considered in the program that generates the search acceleration data; 150831.doc 201211509 b) dividing the electronic map into a set of hierarchical regions such that the navigable segment or Each navigable segment is classified into at least one of each of the levels; c) using a time varying function associated with at least some of the navigable segments of the core network and typically each navigable segment Determining whether the navigational segment is part of a least cost route to at least one of the zones, and recording the determination in the search acceleration data; and d) generating the map material. This method is advantageous because it allows the search acceleration data to be calculated more quickly than prior art methods. Next, it is believed that the search acceleration data is advantageous 'because it allows the route planning using the map material to be performed more quickly in the afternoon. Usually, the search acceleration data is calculated as a plurality of bit vectors. Some embodiments of the present invention may calculate, via one of the bits of the search acceleration data, whether a road segment is part of a minimum cost route from a point navigable segment to a destination region. Those skilled in the art will appreciate that typically each of the navigable segments (or possibly nodes) within the map material has a time varying function associated with it. For example, the time varying function can include the average speed over the navigable segments at various time intervals. For example, the average speed can be specified at 5 minute intervals or the like. It is convenient to generate the core network by removing the navigable segments whose search acceleration data can be recovered later. This method is advantageous because it allows for the determination of the search acceleration data for virtually all navigable segments within the electronic map, thereby enabling the route planning of any navigable segments within the map to be accelerated. Some embodiments of the present invention may utilize any one or more of the following techniques to remove a navigable segment from an electronic map prior to generating the search acceleration data: • satisfy a predetermined criterion relating to the nature of the road; The removal of the portion of the network that forms part of the network is sufficiently small according to a predetermined criterion and can be disconnected from the rest of the network by removing a set of navigable segments that satisfy some other predetermined criterion. Navigable segments; • Folding nodes appearing at joints between navigable segments onto each other under predetermined conditions; and • Where nodes have two or more navigational segments connected to them 'Fold these nodes onto each other. It is believed that such techniques are advantageous because they reduce the number of navigable segments that need to be considered during the generation of search acceleration data, and this increase (possibly significantly increased) can result in the speed of searching for accelerated data. Additionally or alternatively, embodiments of the present invention may utilize any one or more of the following techniques to compress the search acceleration data once the search acceleration data is generated: • calculating the correlation of the bit pairs in the search acceleration data; • aggregating substantially related bits in the search acceleration data in a lossless manner to reduce the number of bits to be encoded; • coalescing the relevant bits in the search acceleration data to perform lossy compression; The bits in the t-synthesis data are reordered according to their correlation into the line 150831.doc 201211509; • Huffman coding is performed on the search acceleration data. In some embodiments, 'substantially related bits can be considered to be nearly related to each other', i.e., there may be a small difference between the search acceleration data to be compressed. The proximity of the search acceleration data that will be coalesced can be adjusted according to predetermined criteria. Thus, embodiments of the present invention having a loss of coalescence further reduce the memory footprint occupied by the search acceleration data at the expense of increasing the processing required to perform route planning using the search acceleration data. Embodiments that re-sequence search acceleration data are advantageous because the efficiency of compression of the search acceleration data by Huffman compression can be increased. According to a second aspect of the present invention, a method of generating map data is provided, the map material comprising search acceleration data configured to increase a speed at which a route can be planned on an electronic map, the method comprising using at least one processing device Processing the electronic map comprising a plurality of navigable segments, the plurality of navigable segments representing a segment of a navigable route in an area covered by the map, the method comprising causing the processing device to: a. process the navigable Segmenting to reduce the number of navigable segments to be considered in the program for generating the search acceleration data by removing the navigable segment to form a core network of navigable segments; b. generating the core network At least some navigable segments and typically search acceleration data for each navigable segment indicating whether the navigable segment is part of a least cost route; and wherein step a. includes any one or more of the following: Meeting a predetermined criterion relating to the nature of the road; 150831.doc 201211509 • Removal of portions of the network from the network is adequate according to a predetermined criterion And a navigable segment that can be disconnected from the rest of the network by removing a set of navigable segments that are full of _----; in a predetermined case, 'will be connected between the navigable segments The nodes appearing at the points are folded onto each other; and in the case where the nodes have two or more of the following navigable segments connected thereto, the nodes are folded onto each other. According to a third aspect of the present invention, there is provided a method of generating map data, the map word comprising search acceleration data configured to increase a speed at which a route can be cut on an electronic map, the method comprising using at least one processing device To process an electronic map comprising a plurality of navigable segments, each of the plurality of navigable segments having a plurality of nodes associated therewith, representing a segment of the navigable route in the region covered by the map and having associated thereto The table is not a parameter of at least a parameter of the n-navable route, the method comprising: a) evaluating the at least one attribute; b) dividing the electronic map into a set of hierarchical regions such that. The Haike Navigate# or the parent-navigable segment is classified into at least one of each of the levels, wherein the classification uses the evaluation of step a to ensure that the navigational segment is associated with a navigational segment such as shai The nodes are balanced on the areas of the electronic map; c) the map material is generated. An advantage of this method is that it can help balance the number of navigable segments that are interspersed between the 150831.doc 201211509, which in turn can help increase the effectiveness of the search acceleration data. . ▲ ^ Repeat steps a) and (4) to meet (4) the predetermined criteria for the balance of the nodes between the zones. For example, a threshold above the number of navigable segments that may be present in a given zone may be the criterion. This measurement can help to ensure that the search acceleration data is calculated more quickly; if the zone 3 has an imbalance of the navigable segments contained therein, the speed at which the search acceleration data can be calculated can be compromised. The attributes may include any of the following: • the type of navigable segment; • the average speed along the navigable segment; • the length of the navigable segment; • the connectivity of the segment to other navigable segments. The method can be configured to determine a map area where travel time will be slower than a predetermined threshold, and the navigable segments within the area can be further separated from other areas of the electronic map. The method can be configured to separate the navigable segments of the island from other regions of the electronic map, which can be performed by determining the properties of the navigable segments as a ferry route. This method is advantageous because traveling to such islands can be slower than other areas of the electronic map, and including such islands can compromise the effectiveness of the search acceleration data and/or can slow the calculation of search acceleration data. According to a fourth aspect of the present invention, a method of generating map data is provided, the map material comprising search acceleration data configured to increase a speed at which a route can be planned on an electronic map, the method comprising using at least one location 150831. Doc • 10· 201211509 The device processes an electronic map comprising a plurality of navigable segments, each of which represents a segment of a navigable route in an area covered by the map, the method comprising: a) Dividing the map into a plurality of hierarchical regions belonging to at least one coarser level and an adjacent finer level, such that each navigable segment is classified into each of the coarser level and the finer level In at least one of the zones, and wherein any one of the coarser grades contains a plurality of zones of the finer level; b) _ for a given destination area, by evaluating whether it should be close to the area containing the destination The regions of the coarser level regions are added to a visibility region and the zones are added when the evaluation is positive, and the at least the coarser region including the destination region is determined to be included. a range of the visibility area of the zone; c) calculating information about at least one least cost route to the destination area for at least some navigable segments; d) wherein processing of a navigation segment includes performing an inverse from the destination area Retrieving backwards toward one of the navigable segments, and substantially only including the navigable segments in the visibility region of the region; and e) generating the map material. One of the advantages of this method is that the use of nearby areas allows the search space used to generate search acceleration data to be constrained, and thus, the speed at which search acceleration data can be generated is increased. According to a fifth aspect of the present invention, a method of generating map data is provided, the map material including search acceleration data configured to increase a speed at which a route of 150831.doc 201211509 can be planned on an electronic map, the method comprising using at least A processing device to process - an electronic map comprising a plurality of navigable segments, each of the plurality of navigable segments representing a segment of a navigable route in an area covered by the map, the method comprising: a). Dividing into a plurality of hierarchical regions belonging to at least one coarser level and an adjacent finer level, such that each navigable segment is classified into the to-be-region of the coarser level and each of the finer levels And any of the areas of the 5th grade that contain the finer level; b). For a given destination area, by evaluating whether it should be close to the coarser graded area containing the target area The zone is added to a visibility area and the zones are added when the evaluation is positive and the at least one of the coarser zone containing the destination zone is determined to be visible a range of regions; c) _ calculating information about at least one least cost route to the region for at least some navigable segments; d) configuring the search acceleration data to include at least some of the visibility regions and typically each Information of the at least one least cost route of the navigable segment to the destination area; and e) generating the map material. One of the advantages of this method is that the execution speed of route planning using the search acceleration data can be increased. Search acceleration data can be considered as a road sign to the destination area. By increasing the number of areas containing search acceleration data to the area contained in the nearby area, it will increase the "road signs" containing the destination area. 150831.doc •12 - The number of districts in 201211509. As a result, the time to generate search acceleration data can be increased, but the effectiveness of using the search acceleration data for route planning will also increase. The assessment as to whether the zone is close to the coarser graded zone containing the target area may be based on a predetermined criterion. This predetermined criterion can be any one or combination of the following: graph theoretical distance, geographic distance, travel time, fuel: consumption, and/or CO 2 emissions. In fact, in some embodiments, the regions adjacent to the coarser graded regions containing the region of interest may be closer. The zone added to the visibility area may include at least one of the following - a coarser level - or a plurality of zones and a coarser level - or a plurality of sections. Included in the material is that at least one additional route other than the above may be used in the search to accelerate the acquisition of the small cost route, which reflects any one or more of the following: The minimum cost route for a given departure point and destination point at different times; • Different small cost routes between the final _ ° & point and destination point for different traffic situations; • Depending on the cost function Different minimum cost routes; between the departure point and the destination point • for a given road network θ θ μ &# 7 how to change the different minimum cost route between the given and destination points; Alternative routes between pairs according to the same cost function; and departure and destination points • different destination points in directions similar to each other. 150831.doc -13. 201211509 Thus, the search acceleration data may include a plurality of "minimum cost" routes, and the parent system is generally judged against a different criterion. One of the advantages of this approach is that route planning with minimal cost data can produce the best route for each discipline. According to a sixth aspect of the present invention, there is provided a) dividing a map into a plurality of hierarchical regions at one or more levels of the hierarchy; b) processing the regions belonging to a particular level of the hierarchy in the order of the hierarchical hierarchy Processing at least some of the zones from the finest level to the most coarse level, and for at least some of the zones, determining which navigable segments enter and/or leave the zone; c) processing such At least some navigable segments of the navigable segment to determine at least one least cost route from the navigable segment to a destination region; d) wherein the processing of the pair of navigable segments includes performing from the destination region in turn toward the One of the navigation segments is reverse searched; e) in the resulting search graph, 'at least one region at the next finer level' is identified as one of the regions of the next finer level, such that each from a given region A least cost path passes through at least one of the zones of the set' resulting in a correlation matrix; f) identifying in the resulting search map which navigable segments are not included in a different From any zone of the zone to another destination, so it can be considered a "non-transport segment" and removes the non-transport segments for subsequent steps to reduce the considerations in these subsequent steps. 150831.doc •14- 201211509 The number of navigable segments; g) wherein the generating search acceleration data comprises using a correlation matrix to assign search acceleration data to the non-transport segments that have been removed in all previous steps; h) Generate map data. Any of the above aspects of the invention may use one or more navigation devices to generate positioning material comprised of at least a series of locations. In the latter stage, the &<bit> can be used to generate a velocity profile from which the velocity profile is varied with respect to time, wherein the velocity profile generated by the class and the location data generating the velocity profile are The navigable segments that appear in it are associated. According to a seventh cancer of the present month, a navigation device is provided that is configured to generate a route on an electronic map using its processor, wherein the processor is configured to: execute on a remote electronic map - route search; in the cost calculation at the node representing the navigable segment in the electronic map processed during Qian Ge, whether the navigational segment connected to their nodes is marked as part of the - least cost route - assessment; and if such navigable segments are present, only those navigable segments are explored. The search may be compromised by a tree search such as A* Search, any other search method described herein, or the like. In other embodiments, the search can include a directed acyclic graph search. According to an eighth aspect of the present invention, the method provides: a method of generating a route: a method of the route, which is performed at a point in the graph tree indicating that one of the electronic maps can be. Performing an A* search in the calculation, and i50831.doc -15- 201211509 includes evaluating the search acceleration data to determine whether the navigable segment connected to the node is marked as part of a least cost route and if such navigable segments are present Explore only those navigable segments. The search acceleration data is conveniently generated in advance, and the search acceleration data is stored together with or in association with the electronic map. This method is considered to be advantageous because it can significantly increase the speed at which the route can be generated on the electronic map. According to a ninth aspect of the present invention, there is provided a navigation device configured to analyze a map material using a processor thereof to generate a route to a destination on an electronic map, wherein the processor is configured to: • performing a route search on the electronic map using information maintained in the map material; • performing a connection to a cost calculation at the node representing the navigable segment in the electronic map during the search Whether the navigable segments of their nodes are evaluated in one of the portions of the search acceleration data that are marked as a least cost route; • wherein the map material includes an indication of whether there is additional search acceleration data from the node to the destination The additional search information provides additional information about the least cost route; and • if the least cost data is available, only those navigable segments with the search acceleration data are explored. This device is advantageous because the indicator provided in the mantle data helps provide information that constrains the number of routes explored by the navigation device. The indicator can include one of the destination visibility areas, and the navigation device 15083l.doc • 16-201211509 can be configured to utilize this additional information about the least cost route when the destination is within the visibility zone. In accordance with still another aspect of the present invention, a computing device configured to perform any of the above methods can be provided. In accordance with a further aspect of the present invention, a machine readable medium containing instructions for providing any of the above methods when read onto at least one machine is provided. According to still another aspect of the present invention, a machine readable medium containing instructions is provided to cause the device or each machine to which the fingers + are read as any of the above aspects of the present invention The computing device is executed. In embodiments in which the method is performed in parallel, the instructions can be read onto a plurality of machines. Those skilled in the art will recognize that many of the features of the above-described aspects of the invention can be applied to other aspects of the invention with the necessary modifications.

In any of the above aspects of the invention, the 'machine readable medium can include any of the following: a flexible disk, a CD, a DVD ROM/RAM (including _R/.RW and Rw). ), hard drive, memory (including USB flash drive (mem〇ry key), SD card, Me_ystick (TM), tight, I·夬flash. Hidden card or the like) 'Tape, any other form Magneto-optical storage, transmitted signals (including Internet downloads, FTP transfers, etc.), wires, or any other suitable medium. Those skilled in the art will appreciate that many methods and/or apparatus in the methods and/or apparatus described herein can be implemented in software, hardware or (d). In fact, the combination of the three may be suitable for use in at least one of the ideas of the present invention. The reference to the generation of the map data in any of the above aspects of the invention may in fact be It is an optional step' and those skilled in the art should understand that this step is entirely optional for the method. In accordance with still another aspect of the present invention, a method of generating search acceleration data is provided that includes pre-processing a navigable segment to generate data. According to another aspect of the present invention, a method for generating map data from a self-positioning data is provided, the method comprising using at least one processing device to process a packet, an electronic map comprising a plurality of navigable segments, the plurality of navigable segments representing In the segment of the navigable route in the area covered by the map, the method comprises: 1 using one or more navigation devices to generate positioning data composed of at least one series of positions; Generating a velocity profile that varies with respect to time, wherein the velocity profiles generated are associated with the navigable segments in which the location data producing the velocity profile is present; 3_ for the navigable segments At least some of the generated search acceleration data, wherein the search acceleration data is for at least one zone in the zone and typically each zone refers to whether the non-navigable segment contains a minimum of one of the zones or each zone for a predetermined criterion a portion of a route of cost, wherein the generation uses a time varying function for the predetermined criterion; and 4· generates a ground data. In the aspect of the invention, references to nodes, lines or roads can be considered as references to navigable segments and vice versa and those skilled in the art should s 150831.doc •18· 201211509 to understand how to make the necessary change. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the claims The reference numerals will be used to identify similar portions and the description of the examples of the various embodiments, and the flowchart of Fig. 19 in which the reference numerals are in the 19 series is referred to. Figure 1 unintentionally shows a Global Positioning System (GPS), a satellite-based radio navigation system that can be used to determine the continuous position, speed, time, and (in some cases) an unlimited number of users. B) The direction is poor. The past, known as NAVSTAR2Gps, incorporates a number of satellites that operate around the Earth in extremely precise ways. Based on these precise commands, GPS satellites can relay their location as Gps data to many receiving units. However, it should be understood that a global positioning system such as GL〇SNASS, European Galileo positioning system, COMPASS positioning system or IRNSS (India Regional Navigation Satellite System) can be used. The Gps system is implemented when a device specially equipped to receive GPS data begins scanning the radio frequency to discover GPS satellite signals. After receiving the radio k number from the GPS satellite, the device determines the exact location of the satellite via one of a plurality of different conventional methods. In most cases, the device will continue to scan to find the signal until it has acquired at least three different satellite signals (note that 'other triangulation techniques can be used to position the plate with only two signals, although this is very example). In the case of performing a geometric triangulation - the receiver uses three known positions to determine its own relative position to the two-dimensional position of the satellites. This determination can be made in a known manner. In addition, obtaining a fourth satellite signal allows the receiving device to calculate its three-dimensional position in the known manner by the same calculation. An unlimited number of users can continuously update location and speed data in real time. As shown in Figure 1, the GPS system 100 includes a plurality of satellites 102 that operate around the earth 104. The GPS receiver 106 receives GPS data as a spread spectrum GPS satellite data signal 1 〇 8 from a plurality of satellites of the plurality of satellites 102. The spread spectrum data signals 1 〇 8 are continuously transmitted from each satellite 102, and each of the transmitted spread data signals 108 includes a data stream that includes information identifying the particular satellite 102 from which the data stream originated. The Gps receiver 1〇6 typically requires a spread spectrum data signal 1〇8 from at least three satellites 102 to be able to calculate a two-dimensional position. The receipt of the fourth spread spectrum data signal enables the Gps receiver 106 to calculate the three dimensional position using known techniques. Therefore, the GPS system allows users of devices with GPS receivers 1〇6

These electronic maps are not only allowed to use the Gps system (or borrowed by other means)

Provided by the computing device. Set (Sat. Nav), the specific example of its navigational attack includes the satellite guide 150831.doc -20· 201211509. The teaching is called riding (PND) n should be remembered, the present invention:: limited to PND, and Hangovers can be changed to any type of configuration that is configured for processing type = normal) to provide route planning and navigation functionality. Thus, it can be seen that, in the context of the present application, the device is intended to include, without limitation, any type of route planning and navigation: whether the device is embodied as a PND, a vehicle such as a car, a portable computing Resources (such as 'execution route planning and navigation software (4) human computer (4)), mobile phone or personal digital assistant (pda) or 祠 benefits or other computing devices that provide this functionality across the network. An example of the navigation device in the form of a PND is shown in Figure la, and it should be noted that the block diagram of the navigation device 200 does not include all of the components of the navigation device and is merely representative of many example components. The navigation device 2 is located within a housing (not shown). The navigation device 2 includes a processing circuit including, for example, the processor 2〇2 L2 2 mentioned above, which is connected to the input device 204 and the display device (for example, the display screen 2〇6) ). Although the input device 2〇4 is referred to herein in the singular, it will be understood by those skilled in the art that the input device 204 represents any number of input devices, including keyboard devices, voice input devices, touch panels, and/or for inputting information. Any other known input device. Similarly, display screen 2-6 may include any type of display screen such as a liquid crystal display (LCD). In the navigation device 200, the processor 2〇2 is operatively connected to the input device 204 via the connection 21〇 and is capable of receiving input information from the input device 204 via the connection 21, and is operative via the respective output connection 2丨2. The ground is connected to at least one of the display screen 206 and the output device 208 to output the information to the at least one of 150831.doc 21 201211509. The navigation device 200 can include an output device 2 (e.g., the use of the sound/sound). While the output device 208 can provide 20 navigation for the navigation device, it should be equally understood that the input ^ can also include a microphone and software for receiving input voice commands. In addition, the sergeant can also include any additional input device 204 and/or any additional output device, such as an audio input/output device. And 操作 operatively connected to the memory call via connection 216, the capital m / will; ° week to send from input / output (1/0) 4 218 to ° / 5fl via the connection 22G to input / output (I / O) Bee 2 1 8, where 1/0埠2! 8 °, connected to the 1/〇 device 222 outside the navigation device 2〇〇. The external "device 222 can include, but is not limited to, an external listening device, such as an earpiece (4)). The connection of the farm 222 may additionally be a wired or wireless connection to any other external device (such as a steam stereo) for, for example, hands-free operation and/or for voice-activated operation, for connection to Handset or headset and/or for connection to, for example, a mobile phone, wherein the mobile phone connection can be used to establish a data connection between the navigation device 2 (10) and, for example, the Internet or any other network, and/or To establish a connection to a server via, for example, the Internet or some other network. The memory device 2 4 contains a portion of the non-volatile memory (for example, to store the code) and a portion of the volatile memory (for example, to store the # data when the program code is executed). The navigation device also includes a UI 228 that communicates with the processor 2〇2 via a connection 23 to allow a removable memory card (generally referred to as a device to be added to the device 2). In the embodiment, the 忒埠 is configured to allow the addition of an SD (Secure Digital) card. In other implementations, s 150831.doc • 22- 201211509 J, the HV can be connected to other formats of memory (such as Compact h (CF) ) card, Mem〇ry StickTM, a memory card, usB (universal serial bus) flash drive, MMC (MultiMedia) card, SmartMedia card

Microdrive, or the like). FIG. 13 further illustrates the processor 202 and the antenna/receiver port via connection 226. An operative connection between 224, where the antenna/receiver can be a (example) GPS antenna/receiver and thus will act as the receiver of FIG. It will be understood that the antenna and receiver' are represented schematically by reference numerals and that the antenna and receiver may be separate positioning components, and the antenna may be, for example, a GPS patch antenna or a helical antenna. In addition, the portable or handheld navigation device 200 of Figure 3 can be connected or "engaged" to a transport tool such as a bicycle, locomotive, car or boat in a known manner. This navigation device can then be removed from the location of the connection for use in the type of navigation or handheld navigation. In fact, in other embodiments, device 200 can be configured to be handheld to allow navigation by a user. Referring to FIG. 1b, the navigation device 2 can include an integrated input and display device 206 and other components of FIG. 3 (including but not limited to, an internal Gps receiver 224 processor 2, 2, a power supply (not shown). , remember the unit of the hidden system 2 ^ 4, etc.). The navigation device 200 can be located on the arm 252, which can be fastened to the vehicle dashboard/window/etc. using the suction cup 254. This arm 252 is an example of a docking station to which the navigation device 2 can be coupled. The navigation device 2 can be coupled or otherwise coupled to the arm 252 of the docking station by snapping the navigation device 200 to the arm 252. The navigation device I50831.doc -23- 201211509 can then be rotated on the arm 252. In order to release the connection between the navigation device 2 and the interface ’, for example, a button on the navigation device 200 (not shown) can be pressed. Other equally suitable configurations for coupling the navigation device 2 to the docking station and decoupling the navigation device 200 from the docking station are well known to those skilled in the art. Turning to Figure lc, the processor 2〇2 cooperates with the memory 214 to support m〇s (Basic Input/Output System) 282, which acts as a functional hardware component 280 of the navigation device 2 and software executed by the device. Interface between the two. Processor 202 then loads from operating system 214 into operating system 284, which provides an environment in which application software 286 (which implements some or all of the route planning and navigation functionality described) can be executed. The application software 286 provides a work environment that includes a graphical user interface (GUI) that supports the core functions of the navigation device (e.g., map view, route plan, navigation functions, and any other functions associated therewith). In this regard, a portion of the application software 286 includes a view generation module 288. In the depicted embodiment, the processor 2〇2 of the navigation device is programmed to receive GPS data received by the antenna 224, and from time to time, the Gps data along with a time stamp indicating when the GPS data was received— It is stored in the memory 214 to accumulate a series of positions of the navigation device. Such storage of a data record can be considered a GPS location; that is, it is the location of the location of the navigation device and includes latitude, longitude, time stamp, and accuracy reports. This series of locations can be considered as location data. In one embodiment, the data is stored substantially periodically (e.g., every 5 seconds). Those skilled in the art should be aware that other cycles will be possible and there is a balance between 150831.doc -24- £201211509 data resolution and memory capacity. Yes, that is, by taking more samples Increasing the resolution of the data requires more memory to maintain the feed. However, in other embodiments the 'resolution can be substantially every: 1 second, 1G second, 15 seconds, 2G seconds, lungs, 45 seconds, i minutes, 25 minutes (or indeed 'any of these cycles between The cycle therefore accumulates the history of the device 2 at each point in time in the memory of the device. In some embodiments, the captured data can be smashed, praised, and praised. The quality decreases as the cycle increases, and at the same time, the extent of the reduction, and the extent of the reduction, will depend, at least in part, on the speed at which the navigation device 200 moves (approximately 15 seconds of the cycle may provide a suitable upper limit). In addition, the processor 202 is configured to record the location of the device 2 from time to time (ie, the GPS data is uploaded to the server in time (6). The navigation device has - permanently connected to the server Or at least the communication page that is usually present (in one case, in %, the upload of data occurs periodically (which can be, for example, every 24 hours). Those skilled in the art should understand that other cycles are possible, And f can be used as a 卜, 田, 丄 丄 丄 上 为 为 为 为Either: 15 minutes, knife hour, every 2 hours, every 5 hours, every 2 hours, every 2 days, every week, or any time between these cycles. In fact, in this implementation By way of example, processor 202 can be configured to upload a line of data in a substantially instantaneous manner, but this inevitably means that the data is actually transmitted from time to time with a relatively short period between transmissions, and Thus, the data can be pseudo-instantaneous. In such pseudo-momental embodiments, the navigation device can be configured to be within #μ01, »L body 214 and/or inserted in 埠228. The card is buffered with GPS clamps and these GPS locations are transmitted when a predetermined number has been stored. 150831.doc •25- 201211509 This predetermined number can be approximately 20, 36, 100, 200, or any number between these numbers Those skilled in the art will appreciate that the predetermined number is controlled in part by the size of the card within memory 214/埠228. In other embodiments that do not have a communication channel that is typically present, the processor can be configured to Upload the record to the server when the communication channel is generated. This can be This occurs, for example, when the navigation device 200 is connected to the user's computer. Again, in such embodiments, the navigation device can be configured to buffer GPS positioning in the memory or on a card inserted in the cassette 228. The memory 214 or the card inserted in the cassette 228 becomes full of GPS positioning, and the navigation device can be configured to delete the oldest GPS position and, thus, can be considered a first in first out (FIFO) buffer. In the depicted embodiment, the track record includes one or more traces, where each trace represents movement of the navigation device 200 over a 24-hour period. Each 24-hour period is configured to coincide with the calendar, but in other In the embodiment, this is not necessarily the case. The server is configured to receive a record of the whereabouts of the device and store this in a bulk data store for processing. Therefore, as time passes, the mass data storage accumulates a plurality of records of the whereabouts of the navigation device 200 on which the data has been uploaded. In general, the server will collect the travel of a plurality of navigation devices 200. The service provider is configured to generate velocity data based on the tracking of the device or each device. The velocity data may include a time-varying velocity profile that displays the average of the navigable segments along the map. How speed changes over time. 150831.doc

S -26- 201211509 Figure 2 shows an example of an electronic map in which the electronic map is viewed on a navigation device across a network (in this case, the Internet). The first step in any of the examples described herein is to generate this electronic map 1900. λ ^ tt " View the map at http.//routes.tomtom.com/. In order to implement the electronic map of Figure 2 that will be used for path selection purposes, the electronic map has U sections. Points, and users of the electronic map typically do not see X to the nodes. 0 and 'nodes, etc. may be commonly referred to as map material. However, for ease of understanding, some of the nodes in the node hierarchy are shown in FIG. These nodes are located at the intersection, end zone, etc. of the road, and are used for the purpose of path selection. When the user asks their navigation device to plan a route between two or more points, The navigation device will typically plan the route between the relevant nodes of the map (although it is possible to plan a route to a group of nodes). Thus, the map material can be used to generate a route based on at least one criterion set by a user of the navigation device. Those skilled in the art should appreciate that electronic maps also include other nodes that provide the shape of the road segment, the location of the entrance to the building, and the like. Thus, each node 300 has at least a single road segment from which the user can travel, and typically a plurality of road segments. For example, the L' node 302 has four such road segments 3〇4a, 3〇4b, 3〇4c, 304d. Each road segment can be considered a navigable segment because it can refer to a route that is not a road, such as a sidewalk, a footpath, a channel, a railway line, a track, or the like. However, for convenience, refer to the road segment. Thus, the map shown in Figure 2 shows its users a number of roads 150831 .doc • 27- 201211509, where each of the road segments is $ t ^ . Each of them represents the area covered by the map. One of the navigable routes in the section. . People have ★ route planning methods (such as the method of coffee, A* method or stealing - method). However, these route planning methods can be extremely slow in terms of calculation time. In the case of us 6 7 仗 Ub 6 636 800, there is no way to increase the speed of this route planning. Female An - Also < ^• Example, the teaching of the δ Hai case is not hereby incorporated by reference. Embodiments described herein may generate a so-called side_file containing search acceleration data in a pre-processing step for accelerating the generation of the route when processing the electronic map. This information can be maintained as binary data in the form of a bit vector; that is, . String with ^ (or its compression encoding). Thus, the side file can also be considered to be map material 'but the side file can be supplied with or without the electronic map (eg, as shown in FIG. 2, some embodiments of the present invention can provide map material) A map that can be separated from the side file, and other embodiments of the present invention can combine the map and the side file data. However, those skilled in the art should understand that if a side file is used, the side file should be associated with an electronic map (for The side file is generated for use together. If this is not done, it is conceivable that an incorrect route will be obtained (for example, a route that does not minimize the cost function set by its user). Further, different implementations of the present invention An example may specify different parameters for generating search acceleration data (in this embodiment, it is a series of bit vectors and will be referred to hereinafter as a bit vector). Thus, if the generated map data is used Subsequent route planning uses different parameters than those used to generate the bit vector £150831.doc -28- 201211509, then the bit vector is not too It can be useful for the route planning. For example, & some embodiments can generate a bit for traveling through the map by car. If the subsequent route plan is used to generate a route for walking, then the car specific bit The vector is unlikely to be useful & in the other example, the % example can produce a bit vector in the case of assuming that the user is willing to travel along the highway, toll road material. In subsequent route planning, if used The request for a route that does not utilize highways, toll roads, etc., may be useful if the bit vector is not & the present embodiment of the month may generate a plurality of sets of bit vectors, each of which" There are different sets of predetermined criteria. For example, embodiments of the present invention can approximately produce a bit vector of any of the following: 2, 3, 456, 10, 15, or more sets. And in order to generate the side file, in the four steps, in the step of Ί 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固 固' Ν 。. Under Referring to Figure $ more detail b This preprocessing produces information that can be used with the map to increase the speed of the route planning method. In the order (which can be recursive), the nodes in the map data are: ":& In the set of layered regions, generated as shown by the dashed lines in Figure 5. Each of the Hai and other regions contains a plurality of nodes. The method moves them | includes more or less nodes (and thus includes Navigation segment), and in the procedure of shifting the boundary, consider the 'number of road segments associated with the nodes. The method - some embodiments are intended to cover the section 150831.doc in any zone. -29- 201211509 The number of points is set to the upper limit. The square will be π, ##万法 can also be determined according to the expected travel time along the navigable section. For example, if the navigable segment stars have a slow average travel time (e.g., a ferry route), they can be moved to a separate zone. Typically, pre-processing is performed prior to the use of map material, whether the map material will be used on a web site or on a device such as a pND. Therefore, the preprocessing step is often referred to as a server side handler. Although any general-purpose device will be suitable for performing pre-processing, those skilled in the art should understand that the higher the performance of the device, the faster the pre-processing is performed, and the X86-based computing device is used for pre-processing. Such truss devices typically perform operating systems (〇s) such as Micr〇s〇 ftTM wi_wsTM, χ, NUX OSX, and the like. However, other embodiments may use other computing platforms such as the RISC architecture. Again, as discussed elsewhere, the pre-processing can be performed in parallel, and thus, the pre-processing can be performed on a plurality of devices or at least on a plurality of processor cores or real processor cores. a pre-processing step of processing each road segment (e.g., 304a-304d) within a zone to determine if it is part of a minimum cost route to each of the number of zones (N) within the map, and Generate a bit vector (the lowest cost estimate). Therefore, for each road segment in the 'bit vector' contains bits for each navigable segment in a region. That is, the bit vector contains W Bits (except for the zone under consideration, each zone), ...° is also 〇 or 1, depending on whether the route is formed to the shortest route of the zone represented by the bit. Embodiments may add extra bits: provide an alternative to 150831.doc 201211509. Explain that additional information, such as headers, visibility regions, and their classes, are described below. More details and familiarity are described below with reference to FIG. This technology should In this sense, the minimum cost route can be determined against several different cost criteria. For example, the minimum cost can be judged against any of the following criteria: shortest distance; shortest travel time; cost is small (in terms of environmental impact) Use minimum gasoline; produce minimum co2', etc. In the previous example, the minimum cost is judged against the minimum travel time. Therefore, those skilled in the art should understand that for a map covering a large number of areas, N is very It may be large, so pre-processing can take a lot of time. 'So, in example maps covering Europe and Russia, for example, there are usually 50,0〇〇, one node with 12〇 , _, _ road segments. Suppose there are 100 zones in the map, then N is equal to 1〇〇, and there are 120,000,000x100 (N) bits belonging to the bit 兀 vector; that is, 12x10 bits are needed to store 99 of each road segment of the map (i.e., one bit. In the case of an embodiment of the invention described below, this map may use an additional storage of approximately 5 〇〇 Mb. WO 2009/053410 discusses methods of assigning speed profiles that provide speed along a route along a map over time. The content of this application is hereby incorporated by reference herein for the purpose of Whether a route constitutes the fastest route to another zone will vary according to time. That is, as traffic density increases/decreases (for example, J50831.doc 201211509 at inter-peak time and the like), use a route It will become less desirable/more desirable respectively. Some embodiments may store a plurality of unit vectors for each road segment. Those skilled in the art should understand that the higher the resolution of the recording speed, the more the required bits are inward. The number is getting bigger. However, 'other embodiments can use time-varying functions to evaluate the fastest route (much as described in Wo 2〇〇9/〇5341〇, when planning a route across an electronic map, it is believed that it is necessary to be able to use the approximate One-hundredth of a second accurate time granularity for route planning; that is, the departure time from a node can be assigned to an accuracy of 〇〇1 second in order to correctly determine the lowest cost route. Therefore, considering this accuracy At the time of rating, it should be understood that the map with 50,000,000 nodes and 12 road segments considered above has 120,000,0002 possible routes through it. When further considering the time dimension, it is possible The number of routes is further increased: 7 (ie, the number of days per week) X24 (ie, hours per day) x 36 〇〇 (ie, seconds per hour) χΐ οο (ie, one per second) The number of seconds) χ12〇〇〇〇〇〇〇2= 870.9 12·0〇〇_〇〇〇·〇〇〇·〇〇〇·〇〇〇〇〇〇 (thousands of thousands) possible routes. At the current processing level and in use at each In the case of exploring a simple method at a time interval, the fee will be approximately 27,616, 438, 40 〇, 〇〇〇, 〇〇〇. The applicants for the map of Europe and Russia are currently growing year by year. This time is further increased. Therefore, it should be understood that a large amount of data is required in order to store and process the data in the pre-processing stage. Thus, embodiments of the present invention use techniques to significantly reduce the pre-processing of 150831.doc • 32-201211509. This specific technique is described in more detail, and some embodiments of the invention may utilize all such techniques, while other embodiments may utilize only some of the techniques. Different embodiments of the invention may use the Different combinations of features. Thus, some embodiments may utilize all of the techniques described to reduce the amount of information. At the other extreme 'other embodiments may not utilize any of these techniques to reduce data. Some embodiments do not calculate a bit vector of a road segment that does not meet the predetermined criteria - as shown by the step (ie, the road segment does not satisfy the nature of the road) For example, if it is not possible to travel along a road segment in a predetermined transportation category, the bit vector of the road segments may not be calculated. Therefore, in the case of the transportation mode, Can & does not calculate the bit vector of the following road segments: • railway; • segments that do not correspond to navigable segments in the map data; • single-row roads in the wrong (illegal) direction; Road segment (for example, pedestrian walking area and sidewalk when considering the driving ability of a car); road segment at the network mr point (that is, it cannot be avoided from the road section); - a kind of technology n_l, material red material road section The size of the network in the part of the route; the number of road segments is reduced. 7 The amount of time spent on cost calculation, as in step 19^= will be reduced. To illustrate this technique, it is also shown in Figure 2, as shown in Figure 2. Road J5083 Jd〇i • 33 - 201211509 There is no way to deal with this minimum network, but the road segment for the minimum cost assessment has been removed from Figure 4. This reduction in network is intended to provide a minimum sub-network with a minimum cost estimate for the sub-network; therefore, those skilled in the art should understand that navigation has been removed to form a core network. The network that is left in mathematical terminology and illustrated in Figure 4 can be described as the component of the largest bidirectional connection of the undirected representation of the largest strong component of the road network of Figure 2. The core network is determined by applying standard techniques to two strong connectivity (also known as two-way connectivity) while adapting to road traffic rules such as turnaround restrictions and local access. Those skilled in the art will appreciate that the connectivity indication is possible in two directions (i.e., from A->B and B->A) between the two nodes. Therefore, referring to both Fig. 2 and Fig. 4, it can be seen that the exitless paths of the 25 〇, redundant ring 252, and the like have been deleted. However, it should be noted that there are nodes remaining at the beginning of the road segment that has been removed (e.g., 400 in Figure 4). This situation is due to the reasons discussed below. Therefore, in the procedure of reducing the network of FIG. 2 to the network shown in FIG. 4, the Navigator segments have been removed, and the search acceleration data of the Navigator segments can be subsequently restored; that is, the network has been The path removes the navigable segments of the portion of the network that are sufficiently small and can be disconnected from the rest of the network by removing a set of navigable segments that satisfy some additional predetermined criteria. For example, the search acceleration data for node 302 can be readily applied to nodes at the remote end of the navigable segment 3, which has little impact on the performance of any route plan. After being reduced to the core network (e.g., as shown in FIG. 4), the 150831.doc-34-201211509 core network is partitioned to provide the zones described above. In the described embodiment, the network is segmented according to a multiway arc separat(R). Those skilled in the art should understand that in this network, if the road segment (ie, arc) divided by the boundary of the zone is removed, the remaining road segment in any zone will not be connected to any other zone. . Splitting the Network One Step 1 906 However, before performing the splitting, the following steps are performed: Separate and partition the island independently. The island tends to slash away from the rest of the network and thereby chain it by means such as a ferry link. These are expressed in a different way than typical road segments (i.e., the average speed is significantly reduced, etc.), and if such links are included in the segmentation, then the method will not perform as well as expected. 2. Shrink the intersections represented by more than one node in the network, the Chen-shaped roads and other joints so that the nodes belonging to the same intersection, etc. do not fall into different zones. 3: Shrink all the navigable segment shared handles with the same feature set (for example, the ferry w is a part of the deaf walking area or the community with the door, etc.): the two nodes that do not have the possibility of turning The connection between the two; I to reduce the network lost to the split system. j custom input size. For example, check 'can collapse node 3 ο 1 to the node immediately below it, ie 两个― # two or two navigation segments, fold 忒4 nodes onto each other . In another embodiment, the 茑浐 seeds + „ & nodes. τ π , and the complex joints between several may include a plurality of points, which can be used to make the complex fields and points (ie, In the case of 150831.doc -35· 201211509, the nodes are folded (this occurs at the junction between the navigable segments) to each other). The described embodiment of the invention uses divide and conquer (divide and (3) nque^ Method 'Overview of the divide and conquer method at http://labri.fr/perso/pelegrin/sc〇tch, the method outlined in this paper divides the map to include several regions that are not based on the region of the map, and It is based on the number of nodes contained in the zone. #Having such organized nodes has the advantage that it can help make path selection using such zones more efficient as it facilitates delivery with similar local searches The area of the diameter. Each node has its own identification number associated with it, and thus, the nodes in the same area have the same number. The nodes belong to the area of [hierarchical level. By convention, the level 〇 is the most rough grade ( In the long distance path selection), the level Li is the finest level. In some embodiments of the invention, an upper limit can be set for the maximum number of nodes and some flexibility below this upper limit is allowed, instead of setting any area The absolute number of nodes contained within. For example, the method can specify the maximum number of nodes per zone to be 100, which can result in the spread of nodes with 6 nodes to (10) nodes per zone. The upper limit is considered to be a fixed number. The nodes are advantageous because a fixed number can result in a zone with a forced shape, which in turn results in a suboptimal path selection when using the zone. Multiple Ranks In the described embodiment, segmentation is performed to provide a plurality of levels (8) The formula 'is conceptually illustrated in Figure 6. It should be clear from Figure 6 that (6) the hierarchical nature, in which the most rough level (〇) is subdivided to provide the level... s 150831.doc • 36 - 201211509 Then divide to provide level 2, level 2 is the finest level. The number of nodes in each zone varies between grades, and is a coarser grade than the lower grades (it tends to cover larger There are more nodes. Because of the towel, the coarser level (eg, level Q) in the described embodiment is typically used for long-range path selection purposes, while the finer level (eg, 'level 2) is used for short-range The path selection - the part of the bit vector of each road segment contains the bits for each of the material levels. The number of bits is the number of zones in each level. To provide the amount of data to be encoded The concept (in an exemplary embodiment, the number of levels will typically be L = 3): • Global level = 0, will typically have 100 zones. • Intermediate level = 1 'will typically have a zone-level of 10 zones (ie, 100x10). • The most detailed level = 2, which will typically have 5 zones for each zone of level 1 (i.e., 10 〇 x 10x5). The use of a P white layer rating is advantageous because it reduces (possibly significantly reduces) the amount of processing required. In the current embodiment described, there are 10 χ 5 区 zones (i.e., '5 _ zones). Thus 'in a squall structure with the same number of zones' would require that the method outlined herein involve 5_ zones. However, in the embodiments described herein, this number can be reduced by reference to nodes in appropriate levels. - Once the various factors of the map are known, then the number of levels and the area of each level

Li will usually be adjusted. For example, how many stores can be assigned to the execution speed of the map and the light selection. Those who are familiar with this technology should have a compromise of 150831.doc -37· 201211509. Because the amount of pre-processing is increased with the pre-#, the map size is changed to keep the data line. Use the map to calculate the area where there are 3 levels in the faster way. However, in other practical cases, there may be any number of levels. For example, it may be approximated by the following number of grades - one, two, 45'6, 7, 8, or 10 〇 using the above examples (usually having 5 〇, 〇〇〇, 〇 In the case of a node and a map of Europe and Russia with 1^0:000,000 road segments, the simplest encoding will use a fixed large J, flat code J_ for each zone-level node ID. - Each road segment of the rank uses a fixed size bit vector. Because of this, it is easy to calculate the size of this basic code as follows: • Each node area ID at level 0 will use 1〇g_2(100) bits = 7 bits. Each node area ID at level 1 will be used. I〇g_2(10) bit = 4 bits • Each node area ID at level 2 will use i〇g_2(5) bits = 3 bits • Each bit vector at level 0 will be used 1 unit of bits (1 area minus 1 for the current area) • Each bit vector at level 1 will use 1 unit of bits (1 area minus 1 for the current area) • Each bit vector at level 2 will use 5 bits (5 areas minus 1 for the current zone). Figure 6 shows the coarsest zone level 6〇〇, which provides 6 zones in the figure. to

S 150831.doc •38· 201211509 6. Each of these zones is subdivided into other zones (in this embodiment, nine sub-zones) as indicated by the dashed lines within the coarse zone level 600. Therefore, six coarse hierarchical regions can be considered as coarser hierarchical regions, and nine sub-regions can be considered as finer hierarchical regions, which are in regions adjacent to the coarser rank. In the described embodiment, another level of subdivision is used, which is also subdivided into each of the regions provided by the dashed lines, thus providing three levels of segmentation, but this is not shown in Figure 6 for ease of reference. Equal grade (but shown in the figure). Other embodiments may of course use more levels (e.g., 4, 5, 6, 7 or more levels) or fewer levels (e.g., 1 or 2 levels). Thus, an embodiment of the present invention introduces a so-called visibility area for a finer level zone, step 1908. The visibility region of the k-region is a collection of (k-i) regions in which the region can be distinguished on its own bit in the flag set. Naturally, the visibility area always includes the (k_丨) area to which the given k-region belongs. In addition, it may contain some adjacent (k-1) regions. The visibility area should be calculated during preprocessing and the visibility area stored in association with the bit vector. Here, the k zone can be considered as a finer zone, and the (k_丨) zone can be considered as a coarser zone. The relationship between the k-zone and its (k-ι)-level visibility region can also be seen from the opposite side: each (k-1) region is aware of its outskirt consisting of k-level regions located in the neighborhood. In this way, it can be seen that the flag set of the road segment no longer has a fixed length throughout the entire map; the fact is that each bit in the 1 zone has a specific length A+B+C+N periphery 0+ N peripheral 1. Where a refers to the most coarse level 'B' refers to the intermediate size area, and c refers to the most fine-grained area (in the embodiment where there are three levels). 150831.doc •39- 201211509 Subsequent preprocessing calculates the visibility area to generate a bit vector before the shortest path calculation. The method of finding the visibility area can be described as follows: In addition, for each area at each level except the top, and using the breadth-first search in the adjacent map of the area to explore each area The neighborhood graph until the following metric exceeds the selected threshold: the theoretical distance of the graph from the node to the current zone and the Euclidean distance from the median point of the current zone; or other distances described elsewhere herein Any of them. Next, for each visited k-zone (the location is close enough to the start zone), the (k-ι) zone it contains is added to the visibility zone. The proximity relationship should take into account both the geographic measure (for example, the distance between the median points) and the map distance. (Thus, if a zone is geographically distant but is linked to the current zone by a quick connection, the zone can be "close". Similarly, if it is difficult to travel between zones, then the zone can be s Forbearance is "distant" (even if it is geographically close)). The exact threshold can be subject to experimental adjustments because it depends on the specific characteristics of the map (such as the average diameter of the metropolitan area), which is most susceptible to the negative effects described above (such as 'increased pretreatment, etc.) . Navigable segments with exceptionally long travel times (such as ferries or roads belonging to pedestrian walks) are hidden during adjacy graph traversal, such that the visibility region is always limited to a single island or belongs to the same region. Small islands. Therefore, the neighborhood formed by the visited area during the breadth-first search. A set that covers a relatively coarser level below the neighborhood, including the minimum 150831.doc -40-201211509 (incluS10n-minimal) set, is called the visibility area. The inverse relationship is called vicinity: the vicinity of the region ρ (on the level) consists of all regions with ρ in the visibility region at the level ζ + /. For k for a particular case' and with reference to Figure 6, an example of the visibility region is as follows: If the minimum distance between each zone 1 and the edge of its visibility zone is determined to be at least 1, then the visibility zone of some selected zone 1 will be 0 area, and (the 0 area can be omitted because it always exists): • 15: (ie, 'level 1 area No. 15 does not show the visibility area, because its own level area can be omitted, Because it always exists). *28: 5 (ie, the visibility area of the No. 28 level 1 area contains the level 〇 area No. 5). · 37: 2, 5, 6 (ie, level 1 area No. 37 has three areas in its visibility area, ie, level 0 area No. 2, No. 5, and nickname) Spear, considering the level The ranks of the districts are neighbors, and each level is also determined, and 1 neighbor. Therefore, as an example, •1: 21,24, 27, 28, 41,42, 43, 51 (that is, for the mth level, the level 1 area is: 21, 24, 27, 41, 42, 43, 51) ° Thus, in this example, it can be seen that 'zone 28 is listed, although it is not in the leftmost row of zone 2. This may, for example, be due to zone 28 I50831.doc 41 201211509 having a fast link to zone 1 and thus being close when considered in terms of time rather than distance. Those skilled in the art should understand that proximity can be judged against other measures such as greenness (minimum C〇2 or its like). Some embodiments may use the visibility area to reduce the amount of pre-processing required to generate the search acceleration data by constraining the search acceleration data calculation. By way of example, an embodiment may use a reverse search from a destination area (e.g., area 24 of Figure 6) to a starting point navigable section (e.g., in area 27 of Figure 6). This reverse search can be constrained by stopping the reverse search when all navigable segments in the visibility region of the destination region are reached via the shortest route. For example, in the case where the visibility area of the area 24 is assumed to be area 2, once all of the navigable sections in the area 2 are reached via the shortest route, the reverse search will stop. Those skilled in the art will appreciate that the shortest route within zone 2 may pass through a zone that is not included in the visibility zone of zone 24. For example, the shortest route between the two locations in zone 2 may pass through zone 1. More specifically, this may be true for the shortest route between the starting point navigable segment in zone 27 and the destination location in zone 24. This route must be considered in order to generate the correct search acceleration data for zone 24. Those skilled in the art should understand that the constrained search described above will produce the correct search acceleration data for the route through Zone 1: within Zone 2 (specifically in Zone 27), using search acceleration data. The search will use the search acceleration data for zone 24; as it advances to zone 1, it will use the search for coarse zone 2 to speed up. Since the zone is not in the visibility area of zone 24, the navigable section in zone i will have the search acceleration data of the coarse zone 2 but not the search acceleration data of the finer zone 24.

S 150831.doc -42- 201211509 Additional or alternative embodiments may also use the visibility area to increase the search acceleration data stored for a given navigable segment. While this may increase the amount of pre-processing required' but it may also increase the speed at which route planning can be performed when using map material containing such search acceleration data. In the case where the visibility area of the hypothetical area 51 includes both the area 5 and the area 4, the accelerated search to the destination in the area 51 will have used the specific acceleration data existing in the area 5 in the area 4; The road segment within Zone 4 has additional search capital added to it's indication that the road segments contain additional minimum cost information to the zone. This additional information can be referred to as related bits. This is considered to be advantageous over the prior art. The prior art would only apply the acceleration data to level 5 in zone 4, thereby having the disadvantage of having a search front that is much wider and close to zone 51. The encoding of the neighbor list is compared to the figure ’ to show more details of the grades that can be used. Level 〇 is the most coarse level and can be considered as level k_l. For the sake of simplicity, only zone 丨 to zone 4 is shown in Figure 6a (i.e., 6〇2; 6〇4; 6〇6; 6〇8). Each of these k_1 zones is further divided into nine zones (1 to 9), which may be referred to as k-level zones or rank zones. In addition, each of these level i zones is divided into four k + 1 level zones (i.e., level 2 zones). Generation of a bit vector Once the network has been partitioned into hierarchical levels (3 in the described embodiment), then it is processed to determine the least cost route to each of the zones and is generated The bit vector of each road segment in the zone, step BIO. Thus, as discussed above, the cost function is used to analyze each road segment in any zone to determine if it is part of the low cost route to each of the other zones 150831.doc • 43- 201211509. Produce a bit vector for each of the road segments, as shown in Figure 7. For ease of understanding, Figure 7 shows a simplified bit vector 0. It should also be understood that the lowest cost route is determined not only for a single time. The segment is calculated for a plurality of time periods (this network is performed as described below for the network shown in Figure 4 (i.e., reduced network). The network in Figure 3 has been moved. Except that part is effectively folded onto the node from which i originated. For example, the end node of the road segment 3〇 shown in Figure 3 is folded onto node 3 〇2 in Figure 3. The 'per-bit vector contains three bars: the leftmost block containing the identity identification number of the node at the beginning of the road segment under consideration; the identity of the node containing the end of the road segment under consideration The second stop 702 of the identification number and the third stop containing the bit vector of the road segment. It should therefore be seen that each road segment is identified by two nodes, and one node is present at each end of the road segment. Use any suitable path selection method to determine a road Whether the segment is part of the lowest cost route. In this particular embodiment, the well-known Dijkstra method is used to explore the entire network. However, various strategies can be used to reduce the amount of processing time. Those skilled in the art should understand that The techniques described for reducing the network will also reduce the amount of processing time. Embodiments of the invention may use any one or more of the following: • Simultaneously calculate all bit vectors corresponding to a region Inputs. In the reverse view, the minimum 150831.doc, 201211509 path tree is calculated for each navigable segment located on the boundary. This method is advantageous because each zone can be processed in parallel to reduce processing time. • Reduce recalculation of similar shortest path subtrees • Do not recalculate the bit vectors that have been generated. Therefore, in summary, an embodiment may perform the following operations to generate bitwise preparation steps: 1 It should be understood that the search via electronic map can be represented by a directed acyclic graph (dag). This graph and the accompanying data structure (turning cost and long extension table) are reversed. 2. Shrink the simple road segments for the finest level (ie, fold the end nodes onto each other, as discussed elsewhere). If the road segment (ie, the path) consists of one or more nodes = 2 All nodes are in the same zone of a given level), and the navigable segments have the same attributes: eg isaferry, "isNoThrough" and "IsNoDriving", then the road segment is called simple. 3. For the parent zone, Whether the head (ie, fr〇m_n〇de) and/or tail (ie, to_node) nodes belong to the area, the road segments of the road network are classified into three groups: exit, entrance and internal roads. Section, that is, if both the head and the tail are in the same area, the road section is called the inner road section; if the head is in the zone but the tail is not in the zone, the road section is called the exit road section, and if the tail In the district but the head is not in the district, the road segment is called the entry road segment. 4. Set special turning restrictions for all road sections leaving the NoThrough and NoDriving areas. The pre-processing routine is performed in a bottom-up manner, with the finest level of division - that is, starting at level 2 in the described embodiment. At each level, repeat the following steps for each zone: 1. Identify and explore the area. At the highest level (e.g., the region in the described embodiment), which is the entire map, at a finer level, it is a subgraph limited by the visibility region of R (as described above). Therefore, at the intermediate level (i.e., level 丨), the following steps are performed only for the visibility areas of the level 含有 areas containing their level 1 zones. At level 0 (should be remembered that it is used for long-range path selection), consider the road segment of the entire map. The entry road section of the visibility area is collected, that is, the node from the outside of the area leads to the road section in the area. The road section is then collected, that is, the road section after the road section. If the head (L 1) = tail (L 2) and the turn from L 1 to [2 is not prohibited, the road segment L 2 is referred to as after L 1 (and L is before L 2 ). In order to find the border road segment, the complex intersection is shrunk into a single node. Ferry routes and road segments with the “NoDriving” attribute are not considered as border road segments. Collecting the inbound road segments in this manner can reduce (possibly significantly reduce) the amount of processing required in the exploration steps described below. The exploration step can reduce the exploration of the map and consider their route to the given route including the route of entry. 2. For each road section of the road, find the root road segment and explore

S I50831.doc -46- 201211509 Number of steps. If the (4) material segment is at least one of the predecessors, the exit road segment is the only root road segment, and the ^H^ 饤仃 early one picking step . Otherwise, the right (four) material segment is bidirectional (that is, the light can be illuminated on both sides 6 (five), then the road segment itself and its opposite (human 4) road segment are taken as the root road segment of the early-exploration step ^ ^ π Helmets left uj right out of the Zen road & early, then each of the front internal road segments (and if there is 'the opposite road segment) to take the root of the separate exploration step: paragraph. Finally ' Regardless of the type of exit road segment, each of the outbound road segments - the extension of the road segment, if it is located at R (1), acts on a separate exploration step road segment. At a finer level (ie, In addition to all grades other than the rank )), the ferry route is specially treated. As mentioned above, the ferry route is ignored when it is true: if the head area of the ferry route does not belong to R In the visibility area, a single exploration step will be performed, where the ferry route is a unique root road segment and the exploration area $ is constrained to the head region itself. 3 • Perform a scheduled exploration step (described below). · Traced from the road segment to the root road in the exploration area The shortest path. At all levels except the highest level (ie, level 〇), the ordering of the road segments from which the individual tracks start will affect the result. Suppose R is the level L area (where L>0), Then, the exit road segment of the level α_υ area is processed first, and then the remaining exit roads at the level L are processed 150831.doc • 47· 201211509 & and processed to the finest level; the internal is relative to the finest level The road segment (and has not been removed) is finally processed. Whenever you encounter a road that has been visited in an earlier tracking, there is no need to follow the path again. While tracking, '6 again The appropriate target bit of the visited road segment is 1. Perform additional actions at all levels except the highest level (ie, level 〇): After the path has crossed the boundary of a certain level L for the first time, Mark the boundary line and all other road segments going to the root road segment with the ansit line flag; mark the shortest path for the u-turn node with the u-turn flag. Finally, except for the finest level At all levels except the fill matrix entry. After processing all the zones of the class, simplify the plot for the next level. First, 'remove all road segments that are not marked as transport lanes. Then, shrink the accumulated new ones. The simple path 'retains the section labeled as a u-turn node, according to the previously removed road segment. Correlation Matrix Some embodiments of the present invention use a correlation matrix that stores the required vector for the road segment. The relationship between the target areas. At each level L except for the finest, etc., a new correlation matrix is generated and used.

150831.doc -48- S 201211509 The matrix is indexed by level π + 〇, and the rows are indexed by level L, and each matrix input is zero or more than 0 + " At lower levels, most matrix entries are equal to the empty set, ie, the matrix is sparse. The purpose of the correlation matrix is to help locate the road segments that have been deleted at an earlier stage. These road segments are not included in the directed acyclic graph resulting from the level L exploration step, but if they are not deleted, they will be included in the directed acyclic graph. More precisely, the correlation matrix is used for a certain level on the road segment in the exploration area j of S (something in Y (where L is not the finest level), which has been deleted) The L zone S sets the bit direction to 罝. For the level 仏 + (four) feet contained in the exploration area of S, the matrix element can, q will eventually be the set of level regions at the boundary of the visibility area of the rule, so that all the shortest paths from (4) (in the reverse view) Middle) through one of their districts. When a moment is generated, all input items are initialized to an empty set. Next, in all ranks L zone S, the following two actions are performed. ^Matrix establishment · For the root road segment (4) and the resulting directed acyclic graph or each of the exploration steps, for each level of the ship included in the exploration area of S, and for each of the R road segments卜 matrix element Μ [foot blade update as follows: use Α table not R exploration area (such as earlier for the grade of Sichuan in the D from / 'trace path to / and check the apricot pot s secret master and check its疋No leave A: If the road section of this road scale 2 is from grade (four) to grade (four) zone r (its... δ is in A, extension 71' Fuhe ancient private gentleman, ^3 is in Yuzhong), Then add to the collection, _ 15083 J, doc • 49- 201211509 'and process the next / '. 2. Read matrix: for each track in the exploration area of S that has been deleted before the start of level L calculation The road segment 'assumes that R is the level (X + i) region where the road segment ends (again, relative to the reverse map). Now set the bit vector bit of the region S on the line to the position of the region τ The logical OR of the meta-vector bit, where T includes all elements of Μ[foot 51]. Note that it will have been directly based on a directed acyclic graph at an earlier level. The bit vector bits of each τ are set according to a similar procedure involving a correlation matrix at a lower level. The exploration exploration step is a directed acyclic loop that establishes the shortest path with the given road segment (pair) as the root. Figure composition. This is achieved by using a variant of the well-known zero-ru method for shortest path (ie, ::cost) calculation. Attribution: Tradition has chosen the "shortest"; in fact, Any one of the factors such as travel time or estimated fuel consumption, or other factors described elsewhere (4), may be freely selected. One embodiment uses the weighted sum of travel time, other penalty terms of maneuvering / Length and suppression of improper transfer and the following modifications to the Dijkstra method. 1. It works on the road segment map, the project is a road segment, not a node. This = access, relaxation, etc. / or traffic extension is used to allow the method to test 2. The target function in the tag is the selection, cost) of the fixed set of vectors with - pair (for the ^ segment of the arrival time slot J 5083), d 〇 c -50 . 201211509 Time slot In order to cover all relevant modes of transportation (free flow 'working day 2 morning peak time, evening peak time, etc.). In the following discussion, we will elaborate on this in the discussion of the cost function in the evaluation of multiple time periods. 3. More than one tag may be stored for the road segment; if the set of pending (unfinished) traffic extensions on the two tags are not equal, then the tags themselves are said to be independent and both In the subsequent road segment 2, the traffic is continuously propagated. Otherwise, if the relationship between the cost function values of the different arrival time slots does not alternate (that is, the '--label is obviously better than the other label), the poor label is discarded. Otherwise, by merging A good value for each time slot produces a new label 'to spread it instead of the original label. The merged label predecessor set is the union of the original label's predecessor set. 4. Generate a special postal turn label on each-two-way road segment. It encodes the possibility of starting a real (non-reverse) route in both directions. Do not pass the =u-shaped turn label, and you can't mark the u-turn label with the general label - and ΛΛ: and its scene > the backtracking phase when setting the bit vector: only at the beginning 'sign no more than the same road segment When the U-turn label is poor, the shortest path is flagged. 5. At a finer level (where the exploration area is limited to a collection of zones), see the border road section as defined above. Once the search reaches all border road segments, a watch c〇mb is created based on the maximum (= worst) cost function value per slot. Next, the label on the road segment outside the cable area is only propagated when leaving the stack at 150831.doc 201211509. The label is propagated if the cost function value in at least the time slot is lower than the current monitor comb. If the exploration area stretches over several islands, a separate monitoring comb is maintained for the mother island. Time-varying Functions Some embodiments of the present invention can calculate a bit vector that exhibits a minimum cost route across a network over a plurality of time periods rather than at a single-time. Those skilled in the art should understand that the lowest cost route through the road network can be changed over time due to the impact of traffic density and the like. Thus, for any node, there may be two or more least cost paths, each of which is for a different time. In this embodiment, the bit vector is not encoded with a time reference as to when the minimum cost path is applicable. The bit vector is only set to identify the navigable segment as part of the least cost path or part of the least cost path. Therefore, when using the least cost data for path selection, the path selection algorithm will have to consider all possible minimum cost paths from the nodes. This procedure is now briefly described with the aid of Figure 7a. In the standard Dijkstra exploration of the network, when the network is explored, the method uses the total cost incurred so far in reaching the point in the network plus the expected cost to be incurred. Thus, some embodiments utilize a function rather than a discrete value to make a cost estimate at each node. Thus, in Figure 7a, each node (e.g., 750) of Figure 751 being explored has a cost function associated with it that identifies the parameters being explored (e.g., time, fuel spent, or the like) How to change over time. Node 750 can be considered a starting node. In this embodiment, the 'starting point node' can be synonymous with the starting point navigable section.

150831.doc 52- S 201211509 The cost function can be associated with a road segment rather than a node. The method then processes the cost of the flower 眷,士,, _ t..., by summing the costs that have been accumulated by the function 15 at the current node, and estimating the cost to generate a new function. The example shown in Figure 7a shows the cost function generated by the search method at node 750 at π), and how the time (y-axis) follows the departure time (X-axis). Variety. It should be noted that the rod-in time is known to increase at points 754 and 756 due to the morning and evening high bee times. In a particular embodiment, the cost function is stored at 5 minute intervals (e.g., the average speed over the road segment); that is, it is a function of a quantization function having a time period of 5 minutes rather than a continuous change. If the road segment is part of the lowest cost route at any time period, then the bit vector of the road segment is set. Projecting Core Data to the Entire Network The above describes how to reduce the network contained in the map to reduce the number of road segments and nodes that must be considered by the segmentation method. However, the nodes that were deleted in the reduction step should be further considered so that the path selection method can still generate routes to or from the deleted road segments and nodes. Thus, the deleted nodes and road segments are assigned to the same zone as the node to which they are connected in the core network. Compression As discussed, the size of the resulting bit vector is very large and therefore requires compression of the information. Embodiments of the invention may perform this compression in different ways. However, one embodiment utilizes various techniques to compress, coalesce, and/or correlate the bit vectors, followed by subsequent Huffman encoding of the bit vectors. Thus, some embodiments may attempt and ensure that there is an uneven distribution of bit vectors, as this may help to ensure that Huffman coding is more efficient than would otherwise be the case. For example, if the bit vector is distributed as follows: 00000____ (49% of the time) 11111 - (49% of the time) ... (2% of the time) then it may be necessary to manipulate the bit vector to have more before Huffman coding Uneven distribution, such as: 0 0 0 0 0 ---- (79% of the time) 11111-··- 〇 9% of the time) ?????---- (2% of the time) Generated Bit Vectors To reduce the amount of bit vectors that need to be generated, embodiments of the present invention may use any of the following strategies: or more: • Do not use zone IDs for all nodes, and only generate regions for navigable nodes ID (for example, ignoring the node corresponding to the railway). • Not all road segments require a bit vector, and the bit vector can be used for decision road segments around the decision node. Decision nodes and decision road segments can be identified by viewing road segment data (as described in this document). There are many possible bit vectors, but some bit vectors are much more frequent than other bit vectors' so special coding can be used for the most frequent bit vectors (for example, 000..000 and 111...111). Not 〇〇〇..·0〇〇 or n〗...丨丨 Most of the bits of the bit vector

S J50831.doc •54· 201211509 It is still often set to 1, and the formula is + Λ times and then becomes 〇. Therefore, the Huffman code of a partial block should encode the bit vector quite efficiently. In nodes close to each other, the bits T m are often the same to I, so differential encoding can effectively encode the bit vector. Different regions may have a more similar bit vector pattern by reordering the destination regions 10 by source region (the idea is described in this document). Or all bit vectors around the road segment of the point should always give 111 ._· 111. He can be used appropriately to encode the bit vector more efficiently. Some of these situations are discussed in further detail below. It is worth noting that the technique described in this paper is intended to reduce the size of the bit inward. However, it should be noted that the use of map data for the purpose of path selection requires random access to the data. In general, the effective encoding of the _ data requires a variable size, however, this will prevent random access to the data. Thus, embodiments of the present invention may use a compromise in which data is encoded into a series of indexed pages and then utilizes variable encoding within their pages. In these embodiments, random access to each page (via a 疋 index) can be achieved. Once the page has been accessed, the embodiment can then decode the entire page. This provides a trade-off between efficiency and map size—increasing the number of nodes per page reduces the size of the map, but slows data access. The present invention - a particular embodiment uses 16 nodes per page. It should be understood that any one node may also have a different number of road segments leaving the node. Thus, even though there may be the same number of nodes, there may be variable road segments per page. In addition to 150831.doc -55· 201211509, different compressions can also occur for each of the bit vectors stored on each page. This structure can result in a map format as shown in FIG. Among them, the number "η" is stored in the header, and the number "η" can be changed for different maps to optimize the performance of the map. Adjusting "η" is a compromise between the size of the map and the speed of access when decoding map data: Large η values will group many nodes together, which is good for map compression, but for random access to data The speed is not good. The η value of J will group a few lang points together, which is beneficial for the speed of random access to data, but is not good for map compression. "η" can be set to, for example, 4, that is, 16 originating nodes (the originating node is at the beginning of the road segment - that is, the column 7 of Figure 7), but should remember Each originating node has a number of arriving road segments (t〇-r〇ad segments), so in the case of assuming an average of 3 arriving road segments, 'every_ means that the storage amount per page is equivalent to ~ 48 road segments. In this format, the data has a different format depending on the level of the encoded region. Figure 9 shows an example of the format of level 0 (i.e., the coarsest area), and Figure 9 shows an example format of areas of other levels. The bit vector and related information are stored in a data structure, and the format of the data structure is shown in FIG. 8. The format includes the following: a header is used for the Huffman tree in the Huffman coding described later. Rib 2; H count 8G4 in each level (in the case where each level has a number of zones)

S I5083J.doc •56· 201211509 is the second of the 'zone neighbor 806 (in the situation of the neighbors

Remap table 808; bit & den hundred +, / work for); area ID bit inward page index (215 and bit vector 812. can hold bit correction, and area ID _ ^ J The poor structure is captured in a small number of seedlings, or it can be kept in a plurality of files. In some embodiments, the head of the icon 8 is followed by other information: • The maximum number of levels • The length of the shortest neighbor list • The length of the longest neighbor list • The byte offset of the section containing all neighbor lists. Keep the information file or each file area *mu * Field tired It has the size to encode the neighbor list first, and is the size of all the lists of codes. Relative to the shortest list length, ^BitsRequired(longestLi^ 疋 the number of fixed bits on the per-list length. Note that if all lists = If you have the same length, you don't need a bit to encode the length. Then you can encode the contents of all the lists. Each list consists of several groups of neighbors: 〇 at the level, 3 elements at level 2. Group, etc. ^Italian, no, code originating area ( Fr〇m_regi〇n) tuple (the other part of the (10) case). It is implied because the list of all areas: 乂 ascending order storage. For example, if the map has ι〇〇χΐ 3 levels of 〇χ5 (100 areas at level 0, 10 areas at level 1, and 5 areas at level 2), Bay 1J: At level 0, store the originating area 1 (in this order) 100 lists), 2, 3 ' ..., 100 list Each of these lists contains 150831.doc -57- 201211509 There are several pairs. • At level 1, store the originating area 1·1 , 1.2, 1.3, ..., uo' 2·1 2.2, ..., 2.10, 3.1, ..., 100 9, 1〇〇.1〇 early morning (1000 lists in this order). Each of them contains a 3-element tuple. At level 2, nothing is stored because it is the last level 'so there is no neighbor. The 4 and the items are stored as η bits. The number of zones corresponding to the level determines the number of bits per level. Therefore, it is possible to randomly access the list. In the case of 3 levels (10)·5, the coding tuple abc will be used for &am p; 7 bits (because there are ι〇〇 areas in the level )), 4 bits for b (because there are 1 area in the level )), and 3 bits for c Yuan (because there are 5 zones at level 2). Example: Assume 100><10><5 zones have the following divisions [100 areas in the rough level, 10 areas in the middle level 1, and 5 areas in level 2 of detail. In the file at level 0, the section containing the list of neighbors will contain: • 1 number indicating the length of the list of 100 zones in level 0. The number of bits is calculated according to BitSReqUired(longestListLength_sh〇rtestListLength). Each number is relative to the shortest list at that level (the shortest list is stored in the header). • Next is the content of 100 lists (100 pairs). The first element of each pair is encoded on 7 bits (because there are 1 area at the level )), and the second element of each pair is encoded on 4 bits (because 150831.doc • 58 · 201211509 There are 1 area at level 1.) In the file at level 1, the section containing the neighbor list will contain ····100Χ10=1000 numbers indicating the length of the list of the areas at level i. •• Next is the content of 1000 lists (1000 3-element tuples). The first element of each tuple is encoded on 7 bits (because there are 100 fields at the level )), and the second element of each tuple is encoded on 4 bits (because in each level 0 area) There are 1 level 丨), and the third element of each tuple is encoded on 3 bits (because there are 5 levels 2 in each level 1 area). In the file at level 2, there is no need to store anything because it is the last level. The header 800 is generally 'the header used in embodiments of the present invention is small, and thus, there is no need to optimize this size in order to reduce its size. Usually, for convenience, all content is byte aligned or word aligned: • (4 bytes) encoded version (increased each time the map format changes) • (4 bytes) Map flag (to turn features on or off, initially 0 ' but can be used later if you need to add optional features) • (4 bytes) Total number of nodes in the map • (4 bits) Tuple) The total number of road segments in the map • (4 bytes) Segment Huffman tree byte offset • (4 bytes) Segment region Binary large object (blob) Bytes 150831.doc -59· 201211509 Offset • (4 bytes) Segment area page information byte offset • (4 bytes) Segment bit vector page information bit group bias Shift • (4 bytes) segment variable size record byte offset • (4 bytes) maximum bit vector page (in bits) (can be used by route planning method at startup) Bad condition of pre-allocated bitstream decoder) • (4 bytes) average bit vector page size (in bits) (for interpolation) Bit vector page position) • (4 bytes) minimum bit vector page difference (to make all differences >=0' thus avoid storing bit sign) • (2 bytes) bit vector The largest size of history (can be used by route planning method to pre-allocate history buffers at startup) • (2 bytes) maximum number of road segments per page (currently unused) • (1 byte) Apollo level of file • (1 byte) bit per bit vector • (1 byte) bit of each bit vector page difference (fixed size record of bit vector page) • (1 byte) bit per large object index (block in fixed size record of area page information) • (1 byte) bit counted per area (area) The field in the fixed size record of the page information) • (1 byte) the bit of each trivial bit vector block • (1 byte) area node page size log one 2 ( 150831.doc 201211509 • (1 byte) bit vector page size log-2() • (1 byte) Number of Huffman trees encoding 10 in the region • (1 byte) Number of Huffman trees used to encode the bit vector history code Huffman tree 802 • Used to encode the road around each node The number of segments of the Hoffman tree: very small, only about ΐ θ codes, only exist in the file of the level 〇

• The Huffman tree used to store blocks of non-trivial bit vectors: Max Treviq ^, the larger the better the compression, the more memory is required in the route planning method (on the map) The trade-off between compression and memory usage in the route planning method) C • S Huffman tree of the difference vector of the bit vector when the historical size is 0: very small, only 3 codes • The history size is 1 bit Hoffman tree of vector difference code: very small, only 4 codes • Huffman tree of bit vector difference code although historical size >=n: very small (the number of Huffman trees is stored in the header • Although there are 3 zone time zone ID Huffman trees in the zone page: very small, only 3 stone horsefields have 4 zone time zone ID Huffman trees in the zone page: very small, only 4 yards There is a Huffman tree with a time zone ID of >=n zone in the field page: very small (the number of Huffman trees is stored in the header). 150831.doc • 61 · 201211509 Zone remapping table 804 and zone ID list 806 Although the zone ID 806 is smaller than the rest of the file format of Figure 8, the zone ID 806 can also be compressed, as illustrated in Figure U. Among them, geographical correlation can be used to reduce the amount of data used. Each zone page stores a list of distinct zones in the zone page. This list is expected to be small in most cases (in fact, many pages are likely to contain only U areas at least level 0). The list of zones has a variable size. It should be possible to randomly access the data in the page (also #, random access) and thus, use a fixed table size to allow this. Each of the distinct zones is sorted by the frequency of the nodes in each zone: List: The first element corresponds to the zone with the largest number of nodes in the page, and the last element of the list is the minimum number in the page. The area of the nodes. For each node in the zone page, the local area m (local to the page) can be used to encode its zone IDe. This is the index of the zone in the page (: is a small integer 'often 〇' because 0 corresponds to the most common area in the area page). The ID of the zone is stored as follows: •: All possible overlaps/monthly orders for the zone in the zone array of the zone ID. The list of zones is the contiguous zone ΐβ in the array. Lists can (and do) overlap. The array does not store the beginning and end of each list (this is done by the area page information table). • The area page information table is a fixed size record table (and therefore randomly available), and each record contains an index in the array at the beginning of the list + the number of items in the list. s 150831.doc -62 - 201211509 • Each node contains a local node ID (local to its page). Each of these concepts is further defined below. A list of all possible regions of the region array code page. It is a simple array of zones, where the list of zone IDs can overlap. Its size should be small because the lists overlap. The array of regions is further described in the section area page information. Area Page Information Use the 2 Blocks in the Fixed Size Record of the Area Page Information Table to specify the area page. The list of area IDs in the table: • Area count (the number of areas in this page, expected to be small). • Offset in the array of zone lists (where the list of zones begins). In an embodiment, this is as depicted in FIG. Offset block pointers to the array of regions: (for example) assuming that there are always less than 256 regions in each level (which is a reasonable assumption), a fixed-size record with 1 byte per region is sufficient (But if the maximum of 256 zones per level is considered too restrictive, then each zone m is greater than 8 bits is easy to implement). The zone count in the zone page table record indicates how many zones in the array are to be considered at the specified offset. If several zones have the same list, they can point to the same location, which should be = compact, as we can expect many pages to share the same list or share portions of the same list. This is explained in more detail with reference to Figure 9, which shows an embodiment of a page having two nodes, for example (4) to group 512 nodes together. 150831.doc •63 · 201211509 Note. The array of Italian zones is _ compact, because several pages can point to the same-location or overlapping location in the array (large objects in the location marked in the figure). In fact, increasing the number of pages may not increase the size of the array, as each page then overlaps over fewer regions, so the likelihood of combining is reduced. Therefore, the array should allow for the creation of many pages without the need for too much map space' and the multi-memory on the device to which the generated map material is loaded. The &" method is to make the array containing the list of zone IDs available: the method is to reuse the same (four) list as often as possible in the array. This method freely reorders the last two elements of the list because it does not affect the size of the Huffman code. For example, when a list contains 2 regions 1 and 34, the storage list 10, 34 or 34, 1G (independent of frequency) is equivalent, because the Huffman tree is in all conditions when there are only 2 nodes. Only one bit is used below. In other words, for the last two zones, the requirements for sorting by frequency are relaxed. Similarly, the list of 3 elements 10, 34, 4〇 can also be stored as 1〇, 4〇, 34, because only the first code 1〇 (most frequently) will use i bits, and other codes Both 40 and 34 use 2 bits (independent of order). Thus, looking at Figure 9, it can be seen that array 900 stores two values: the length and the offset from the beginning of the zone data. Because of the first column (3: 〇), this refers to the three pieces of data from the beginning of the file (ie, 1, 34, 34, 40). As another example, the array round entry (1:2) refers to a single zone (ie, length 1) 'where the offset from the beginning of the archive is two; (ie, zone 40) 〇150831.doc • 64 - 201211509 In an alternate embodiment, the area page information is encoded according to the following method: This section encodes the number of sub-areas in each zone. The number of sub-zones can be variable in each level. However, the number of sub-zones per level is often constant. The number of sub-regions is encoded with respect to the minimum number of zones at each level and using 1 〇 g 2 (max_iuimber_〇f_regi〇ns-min_number_0f_regi〇n) bits. So if the number of zones is constant, then one bit is used to encode the zone count and this section is empty. The minimum number and maximum number of zones are stored in the header of the side story. Encoding of the zone neighbor section (discussing the neighborhood with respect to Figures 6 and 6a) This section encodes a list of zone neighbors at a more detailed level L+1 for each zone level at a given level L. For example, the level [Call Area 3.9 may have the following list of neighbors at level L = 2: 3 5 4 3 6 3 3.6.4 4.7.1 4_7.3. As discussed elsewhere, the list of neighbors can be used to increase the speed of pre-processing used to generate side files or files on each side. This section is split into 2 subsections: • A subsection that is used to encode the length of all neighbor lists (and the number of zones at a given level). Encoded relative to the shortest list. The length of the hai, and then, the number of bits is calculated as 丨 (gth-longest_list-length-shortestjist). If all 'monthly orders' have the same length, then one bit is used to encode the length (and therefore the section is empty)^ to encode all neighbor lists (with the number of zones at a given level) As many sub-sections. The code for the area ID remapping table 150831.doc •65- 201211509 This section is only encoded in the side file of level 〇. It encodes a two-dimensional table that is used to reorder and coalesce the bits in each of the regions at level 0 (to effectively encode the bit vector, which is further described below in this document). Meta reordering). The reordering and coalescing of the bits in the bit vector is performed to optimize the Huffman encoding of the bit vector. This table is used by the route planning method to find the location of the bit to be decoded in the bit vector when the following is known:

• Origin node ID of the current node • Original arrival bit (t0_bit) index (ie, the bit index after the de-aggregation bit vector bit) The two indices of the two-dimensional table are:

• Originating Zone ID • Destination Bit Index (District of Destination) This section consists of 2 subsections • A section for encoding the number of coalesced bits of each zone at the level 〇. The number of bits used to encode each number is l〇g_2(max_number_〇f_c〇alesced_bits) • The area & used to encode the bit remapping table. Because the target does not change when the path is selected (the destination remains the same when the path is selected) 'but the origination area (1) changes (depending on the node being explored when the path is selected) 'matrix by purpose The column of status elements is stored. In each column, the number of bits in each originating zone is reordered. The route planning method should normally only load the destination W column corresponding to the given path in the path selection s 150831.doc * 66 - 201211509. The route planning method does not require the entire two-dimensional matrix to be stored in the redundant body. The route planning method can randomly access the list. The number of stitches used to encode the per-remap input is calculated as (4)" (the maximum number of coalesced bits). Figure 10 extends the bit vector segment 812 of the archive shown in Figure 8 for the level 0 region (see Figure 6). It can be seen that each page contains a road segment count, a zone ID, and a bit vector. Figure 11 expands the bit of the slot shown in Figure 8 for a level other than the level ,, the quantity section 812. It can be seen that for other zones, only storage location 7C is 1 and no road segment counts or zone eggs are stored. This is because the region number (region__) for each level at the finer level is stored in the side of the level 稽. The reason for this storage is to reduce the number of files that must be accessed during any route planning using the side slot. The code table 810 of bit vectors 810, 812 contains a fixed size record. The originating nodes m are grouped together in a page having 2n. It is convenient to group data into pages with multiple consecutive nodes because the expected bit vector has a similar pattern for several road segments in the same neighborhood. It is possible to encode several road segments by difference (in _) and achieve good compression. In the face, from the female 1 cheek, there is a difference between the node ID of the node in the page. Another aspect of the information that means the access-road segment needs to decapsulate the data of several road segments and directly store it. take). The decapsulation of several nodes or road segments may be considered acceptable as 15083I.doc •67· 201211509 because: the information for accessing a road segment or node can be cached, and the amount of material read : Shake "Not useless. It may be the following: This extra ▲ will be useful soon (this is similar to the read-ahead parameter of the disk cache). 2" Dijksti*a A path selection comparison The path selection using the bit vector reduces the size of the extended search by an order of magnitude. Hunting by grouping data by page 'only a small portion of the map still needs to be decoded (along the page of the actual path). Thanks to the differential compression of the pair and the bit vector, it should significantly reduce the size of the encoded data. Page salt J index size 'Because as described, the data will be stored in the side file. The parent record in a table 810 contains a "difference" block, which is used to find the position of the start of the variable size of the mother-page (relative to the difference between the interpolated positions). The number of bits for each difference is stored in the header. To access the zone ID and the bit vector 812, the decoder can calculate the estimated offset of the start page by performing the following linear interpolation: interpolated_offset = from_node_id, avg_page_size where avg_page_size is the average of the bits stored in the header Page size (may be fixed point to improve accuracy). The offset of the data can then be calculated as follows: offset = interpolated_offset + min_delta + delta 15083l.doc -68- 201211509 where min_delta is the negative of all pages T all the difference fields in the header), and the difference is stored in瑕] Value (Make • J tta /f ^ JS., the unsigned field in the page. The nun-delta value ensures all the difference field numbers).勹 ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( The poor material of the origin (the area ID of the originating node and its attached road segment at all levels will therefore be used for all levels.) Index side variable size record storage: • Page number - for the entire page indication Whether the node in the page is part of the code; • the number of road segments around each node in the vector page (stored only at level , because it will be the same for all levels); The zone ID of the originating point of t is one for each level (for all the funds of the level 5, stored in the slot of level 0), only the road segment data of the node of the section in the page at the level i) Around the point (only in the bit vector with > 2 attached tracks. This is the largest part • The number of road segments around each node is encoded for each of the 2n nodes in the bit vector page In one case, Hoff’s code is on the road of “„ The number of this #讯麟 specific ^ all grades and it is only stored in the file of the level ( (ap_〇_* da〇. 15083 丨.doc •69- 201211509 know the number of road segments around the node To decode the bit vector (see 1000, Figure 10). This information is repeated with information already present in other buildings' but it makes it easier and faster to decode the bit vector in the page without having to find it elsewhere. A small increase in size provides an increase in performance. The encoding of the zone ID in the variable size record encodes the zone of the node in the variable size record after the number of road segments around the parental point is 1 〇〇〇 ID 1002. In order to perform path selection using the bit vector generated in the preprocessing, it is usually necessary to access the area ID 1002 at all levels of the given node, and the area IDs of all levels are stored in the same file close to each other, Instead of being split into different tables of each level, there are 2n nodes (for example, n=4) and there are 3 Apollo-level bit vector pages so the node ID will be stored as follows: node#0: local region Id lev El O local_region_id_level_l l〇cal_region_idJevel_2 node#l: local_region_id_level_0 local region id level l local_region_id_level_2 node#2: local_region_id_level_0 lcal_region_id_level_l local_region_id_level_2 node#15: Iocal_region_id_level_0 local_region_id_level_l local_region_id_level_2 In addition: • Around a node with 1 or 2 attached road segments, Nothing is encoded (ie, for nodes that are stored as the number of attached road segments). • When a bit in the page number is set at a given level, then all nodes are known to be in the same zone ID at the other level, and then only the zone ID of the 150831.doc • 70-201211509 class is encoded. One attack f β person (for the first node with > = 3 attached road segments). The number of bits 7 用 of the cool & m ^ r wood coding area ID is log_2 (regionCount-l) 〇 • In addition to the first node encoded by the area ID in the page, after encoding each area ID Encoding - bit. This bit indicates whether the area (1) is the same as the previously encoded node (1) in the same-level. When this bit is set, 'the zone ID does not need to be encoded because it is the same as the previously coded one of the ranks. When this bit is 0, the area m is encoded by 丨 og 2 (regionCount-丨) bits. Since many consecutive nodes are in the same-region, it is often necessary to only i bits to encode the region ID. The Huffman coding of the index of the region is valid because: • The regions are sorted by frequency in each zone page (so the local index is more frequent than the local index 1 and there is a difference for each number of zones in the page) a specialized Huffman tree (there are one Huffman for three regions in the page, one Huffman tree for four regions in the page, etc.). The Hoffman tree is small, and It is thus possible to store several Huffman trees without using a large amount of memory. • In any case, 'at least at level 0' with 3 zones or more than 3 zones should be quite rare (but at other levels) It is not uncommon. The variable size record allows the encoded mother-variable size record to contain the bit vector of all road segments around the nodes in the page. Only with 3 or more attachments Line (the road segment is again) 150831.doc 201211509 The code point vector around the point of the lang. • gt For a point with 1 or 2 attached roads & points, the path selects 14 to remove the bit vector Values 111... 111) Concealed to their nodes. ; does not code to reach the node. Referring to Fig. 7, the phonetic should be sounded, and the two are designated by the two nodes - the road segment'. There is one point at the mother end of the k road. Therefore, when considering the direction, the head # ... T at the beginning of the direction is called from_node, and the point at the end can be called to_n〇de. The various properties of the bit vector are made (4) within the encoding to make the encoding efficient: • Many of the bit vectors are 〇〇〇·..000 or ill.-.111. • For other values of the bit vector (ie, non-000,000 or 11 ι···ι 11), there may be duplicates and the same value will likely be repeated. Encoding the bit vector as a first Huffman code and optionally other Huffman codes. The first Huffman code indicates whether the bit vector is: • For a trivial bit vector 〇〇〇·_·〇〇〇 Code 0 • For the ordinary bit vector 111...π 1 code 1 code 2 ' is used to indicate that non-trivial bits have not been encountered in this page. In this case and only in this case, there are other Hoffman stone horses to encode the newly encountered bit vector. • When the bit vector is the same as the bit vector previously encountered in the current page (ignoring the trivial bit vectors 000..·000 and 111.·· lu), Shima >=2. This code therefore uses the history of the code previously encountered on this page 150831.doc -72· 201211509. The code is thus actually indexed by the history of all previously encountered codes. In addition to this Huffman code, it is only necessary to encode more information (code = 2) in the case of non-trivial bit vectors not found in history. In this case, 'immediately after Huffman code == 2' the code has: • No locator element • Used to hunt the bit vector of the n-regions encoded by the N-bit block The code (Ν and η are given in the icon head). For example, using a block of 11 bits to encode 1 block (99 bit vector) requires encoding 9 Huffman codes (9XI 1 = 99). Since most of the bit vectors contain zero or contain 1, no positioning element indicates whether the bit vector is stored as negative. This makes it possible to store most of the codes containing 〇 in the Huffman tree (hence the Huffman coding of the improved block). Only if the size of the block is smaller than the number of the area, there is no positioning 兀, this is actually the situation at the level ,, but at the level 〖 or 2, the entire bit vector may be encoded in only 1 block 'So no positioning element is not needed. If there are 100 zones; Ν = 100 (hence, a bit vector of 99 bits), then the first block encodes the bit to the destination area, the second block encodes the area 12 to 22 'etc. . In the first block, LSB(()xl) corresponds to the destination area 1 'lower-bit (0x2) corresponds to area 2, the -bit (4) corresponds to area 3, and so on. The depth of the historical array is the number of previously encountered distinct bit vectors in the page (regardless of the trivial bit vector 150831.doc -73- 201211509

〇〇〇...〇〇〇 and 111...111). When the history vector contains one element, one element, two elements, three elements, etc., using different Huffman trees = equal Huffman tree multiplication is acceptable because all Hoffman trees are 5 'And thus does not require a large number of registers: J When the history has 0 elements, then 000...000, for 丨JL 2. Huffman tree has 3 codes·· for 111. 1. For the new bit vector, when the history has 1 element, the Huffman tree has 4 codes to delete... G, for U1·. 2, for the new bit to the 2nd, for the element with the history of the same as the bit vector 3. When the history has two elements, the Hoffman tree has five codes: for the 〇〇〇.. side of the G, (four) (1).. Chuanzhi 1, for the new bit Xiangdan 2, for the elements in history #〇 The same bit vector 3 is for the same bit vector as the element #1 in history. and many more. The pre-"bits are small in size to one page (for example, 2n originating nodes), so the number of Huffman trees is expected to be small. Fire however, it is possible to limit the size of the Huffman tree to a maximum: for example, a single-Huffman tree (value η stored in the head of the map icon) will be used each time the history contains more than one element. This code encodes only the distinct bit vector + some codes in each page. : In the case of large index pages, the code is more efficient in size, but generation 4 is slower in decoding in order to use the bit vector for path selection (more bit vectors in the page are to be decoded). £ 15083l.doc •74- 201211509 Statistics This is a detailed statistical feed for the format of the Netherlands, Belgium and Luxembourg in 254 districts (1 rating). Use the following input parameters: Number of bits per bit vector block: 11 Number of nodes per bit vector page: 2Λ4= 1 6 Number of nodes per page: 2Λ9 = 512 Provide statistics to give in map size The concept of the map form, and based on some actual data to illustrate the description of the map format: Node count.............................. 1598632 Line Tf number.............................. 1598632 (100.000%) Skip the line around the node with 1 line · 220180 ( 13.773%) Skip the line around the node with 2 lines: 727138 ( 45.485%) Statistical feed at the level = [0]. Map counter 87437736 (100.000%) Coded ordinary arp flag 000 .·.000 1310914 ( 31.651%) The coded ordinary arp flag 111...111 913348 ( 22.052%) The encoded arp flag in history 362432 ( 8.751%) is not encoded in the history of the arp flag 607717 ( 14.673%) Negative block 235171 ( 5.678%) Map size (in bits) ........................87437736 (100.000%) Global standard Head 496 (0.001%) Hoffman Tree 28808 (0.033%) District II Large objects.............................. 52664 ( 0.060%) Area Page Information 56216 ( 0.064% ) arp Flag Page Information 2497880 ( 2.857%) Variable Size Record 84801672 (96.985%) Line count around the node 2847844 ( 3.257%) Node Area ID 2112451 ( 2.416%) arp Flag 79841370 ( 91.312%) Code Ordinary 000 ...000 1683322 ( 1.932%) Code Ordinary 111 ...111 1S26696 ( 2.0893⁄4) Found in the history of 1680053 ( 1.908%) Not found in history ..............74 6572 99 ( 85.38 3% )找到History found in the code 1463183 ( 1.673%) No locating element 607717 ( 0.595%) Block 72586399 ( S3.015%) -75- 150831.doc 201211509 All sizes are in bits. The total map size is 87,437,736 bits (1〇, 929, 717 bytes). Indentation reflects the hierarchy. The variable size record information is the maximum slice information (96.975% of the map size). ^ In the variable size record, the sub-item (indented) gives more details. The bit vector is the largest piece of information (91.312%) to be stored in the variable size record. And in the bit vector, the non-trivial bit vector that has not been encountered in history constitutes the largest part of the map (83.〇15%). Statistics on the Hoffman Tree This is a statistical analysis of the Hoffman tree when the Netherlands & Belgium and Luxembourg were coded in 25 5 districts (ie, 'for the map information shown above'). Huffman tree of the number of road segments around each node - one-ί Hoffman tree: NrLines] - Bits: 1 Value 3 code bits: 2 Value 2 code bits: 3 value 1 code bit : 4 value 4 code bits: 5 value 5 code bits: 6 value 6 code bits: 7 value 7 code bits: 7 value 8 code 0 10 110 1110 11110 111110 1111110 1111111 Most nodes have 3 attached The road segment, but in the second and third positions in the Hoffman tree, we found that there are two attached roads # and one attached road segment (which is not a decision node). Huffman tree of non-trivial bit vector block This is the largest Huffman tree' because the storage block of the trivial bit vector is the largest contribution to the map size (in the case of the Netherlands, Belgium and Luxembourg 255) It is 83.015%). 15083l.doc

S 201211509 ---[ Huffman tree bit: 1 value bit: S value bit: 6 value bit: 6 value bit: 6 value bit: 6 value bit: 6 value bit: 6 value Bit: 6 Value bit: 6 Value bit: 7 Value bit: 7 Value bit: 7 Value bit: 8 Value: Non-trivial Arp flag block 0 code 0 1 code 100000 2 code100001 4 code 100010 8 code 100011 16 code 100100 32 code 100101 64 100110 512 code 100111 1024 stone horse 101000 128 code 1010010 256 code 1010011 38 4 1010100 5 code 10101010 cut, too large value value value 4 4 4 4 4 2 2 2 2 2 Element Element Bits Bits 1534 Code 111111111111111111111011 1717 Stone Horse 111111111111111111111100 1741 Code 111111111111111111111101 1830 Code 111111111111111111111110 1973 Code 111111111111111111111111 Store all blocks formed by 〇 as the most frequent type, and according to the above Hoffman tree It is encoded with only 1 bit (this means that even if the trivial bit vector 〇〇〇..000 is not block-coded, 50% or more blocks are encoded with a value of 0). This is because most non-trivial bit vectors contain • most 0 (and a few 1) • or most 1 (and a few 〇). The encoding scheme negates (~) contains most of the 1 bit vector, after 'bit In most cases, the coding block of the meta-vector is only a 1-bit bat. The next most frequent block is only 1 bit (1, 2, 4, 8, 16, 32, 64·..). It has more or less the same pace' and therefore has the same (or nearly the same) number of bits. ''Hoffman tree of ID in this area is stored in each page by frequency, so you can see that the area ID of other areas is 150831.doc -77· 201211509 Less bits (in fact, only the i-bit different Huffman trees correspond to pages with 嶋, two regions, five regions, etc. ---[Hoffman tree: .Regions 0] meta-bits Value value code code ο 1 ---[Huffman tree: Regions 1]--- Element element bit position bit element element bit position bit element element element Bit value value value value code code code ο ο 1 1 0.......... Man value value value 1 I Huo 1 2 3 4 4

ο 10 no 1110 1111 -1 code code code code eg R1o 1 2 3 4 5w............ Man value value value value value ¢ 12 3 4 5 5 ο 10 1.10 1.1 .10 11110 11111 The code 〇 (meaning the trivial bit vector 〇〇〇...〇〇〇) is the most frequent (and in most cases 'encoded only by the 丨 bit). The code 丨 U ten 凡 兀 vector 111...1U) The U of W (four) is only encoded in i bits). Again frequent code (7) pairs are coded by block with a non-trivial bit vector 1 (> 2) for the bit vector found in history. s 150831.doc • 78 · 201211509 f#Value value f# Value value ^122 Fu 1233 Huo Huo, Yuan Yuan Yuan | Yuan Yuan Yuan j bit position j bit position

ArpiTlag—Ο]-0 code 1 yard 2 yards

ArpFlag_l] Weight 1 stone · ί2 code 3 code 0 10 11 0 10 110 111 £#value value ^^^£#-value value value value value t# value value value value value value value husband PH2344 husband 1234 5 5 husband 1 2 345 6 δ 霍霍霍|元元元元~元元元元元,元元元元元元一位位位位位位位位位位位位位位位

ArpFlag_2] 0 yards 1 stone 4 2 yards 3 yards 4 yards

Arp.Flag_3 ] 0 code 1 code 2 code 3 code 4 code 5 code 0 10 110 1110 1111 0 10 110 1110 11110 11111 ·· ArpFlag 4]--- 0 code 0 1 code 1 〇 2 code 110 3 code 1110 4 code 11110 5 code 111110 6 code 111111 - ί元元元元元元元 tj bit bit bit bit bit | tree ................ @夂值值值值Value value value 2 2 2 4 4 4 5 5 ArpFlag 〇]--- 0 code 00 1 code 01 2 code 10 3 code 1100 4 code 1101 5 code 1110 6 code 11110 7 code 11111 input parameters to the ground. The effect has a number of input parameters that control the file format shown in Figure 8 and can affect the map size. Adjustments to these parameters can be a compromise between map size and memory usage (or parameter dependent). Embodiments of the invention may use the following input parameters: • Area page size • Bit vector page size • Bit vector block size • Bit vector Huffman code count • Area Huffman code count bit vector block size Influence value map size (bits) 4 35548192 5 33648792 6 32290344 7 30853616 3 31103200 9 30436696 (default) 10 30051792 11 29266784 12 28934696 Increasing the Huffman block size of the bit vector improves map compression. The higher the block size, the better the compression. However, increasing the block size comes at the cost of requiring more memory to store larger Huffman trees with 2Λη values. The table above illustrates this situation. The impact of this parameter is expected to become more significant when optimization is introduced to remap the zone ID for each source zone: this optimization will hopefully result in a significant map size when using large bit vector block sizes Reduced. Effect of bit vector page size 150831.doc -80- 201211509 Value map size (bits) 2Λ1 55563944 2Λ2 42502936 2Λ3 34Β98840 2Λ4 304366% (default) 2Λ5 27389952 2Λ6 25165032 2Λ7 23635936 Increase page size to help better compression map. Unfortunately, large pages make the path selection method slow down the decompression of the data in the file format because the access to the bit vector of the random road segment requires decoding all the road segments in the page. The table above illustrates this situation. Bit vector Huffman code count effect value map size (bits) 1 30366920 2 30748024 3 30634168 5 30504504 Ί 30457944 9 30436696 (default) 11 30423688 Increasing the number of bit vector Huffman codes helps to increase slightly Compressed and this is illustrated in the table above. Increasing this value has almost no disadvantages, because the Huffman trees are small anyway. Adding to more than 9 Hove Island trees (preset) does not provide any significant improvement. In the case where the bit vector page is large, it may be more efficient to increase this parameter. The bitwise vector in the coalescing and reordering bit vector has a pattern. Each source region (also gp, the region of the node where the bit vector is stored) is significantly different. The number of bits used to store the N-bit vector of bits can be reduced by storing a small translation table for each source region. These tables perform two functions, which are further described in this section: • Bit coalescing • Bit reordering can intuitively understand this idea as follows: When in Spain, it is clear that the road segment leads to Sweden (Target 1 for Sweden in destination area) is also likely to lead to Norway (ie, 'the destination for destination Norway is then also υ. If another road segment does not lead to Sweden (bits, then in most In the case of the situation, it does not lead to Norway. So when in Spain, the values of the bit vector bits of Sweden and Norway in the destination area are almost always equal. In fact, for many destinations, σ 'is always even strictly equal. Which bits are sufficiently related to which one depends largely on the originating area. For example, 'When in Finland, the correlation between the destinations of Norway and Sweden is much smaller. Another-face' The destination area of Spain and Portugal is likely to be (10)% related (or at least very close to 1%). The bit coalition utilizes this position 亓 θ 4 & 疋 total 疋 equal (completely related) Nature. The elements can be clustered into a single imitation; the early bits are reduced. The coalesced bits reduce the number of bits to be encoded in each region. The bit reordering takes advantage of this - this - the correlation of the two 7L is quite high (but not 1 0 0 % correlation) of the nature of the way to the county, in order to optimize the Huffman stone of the bit vector (and / or reduce the size of the Hoffman tree |, the size of the A tree) Shuffle the bits. 150831.doc •82· 201211509 (3) ~__________+ The reordered bit I is the block by Huffman.

ReorderBits〇 (2) (2) i---- Agglomerated bits I completely related to the group of bits + are agglomerated into a single '~ bit. Λ \. I \. I \· I \. CoalesceBits{) \ . Λ_____ * The original bits to be coalesced + reordered i Calculate all before calculating the table for coalescing the bits and reordering the bits The relevance of all bit pairs in the originating zone. The number of distinct pairs is: C(N, 2)=N!/(2!*(N-2)!)=N*(N-l)/2 ... where N is the number of zones. Therefore, when the number of zones is high, this number is quite awkward. Calculating all bit correlations is the slowest part of the method of generating the slot format shown in Figure 8. The complexity of this method is ηχΝχΝ, where η is the number of bit vectors and ν is the number of regions. For each bit pair in each zone (ie, the pair of distinct rows in the bit vector), calculate the three-dimensional table: bitCorrelation[fromRegionId] [bitl] [bitJ] Each entry in the table contains The structure of the four fields, the count: • the number of bitl=0 and bitJ=0 in all the bit vectors of fromRegionld • the number of bitsl=0 and bitJ=l in all the bit vectors of fromRegionld • all bits from fromRegionld Number of times bitl=l and bitJ=0 in vector • number of bitl=l and bitJ=l in all bit vectors fromRegionld 150831.doc -83- 201211509 Although the computational cost in terms of processor time is high (and therefore slow), However, it is easy to parallelize this program because the bit correlation for each of the origin regions is completely independent of the other origin regions. Embodiments of the present invention use multiple threads to speed up the calculation of the correlation of all bits to effectively use SMP (Symmetric Multiprocessing) machines. In a system, a single CPU machine calculates the bit correlation of the Netherlands, Belgium and Luxembourg with 300 zones taking about 8 minutes. However, the parallel processing principle (state (4) (iv) is well scaled, and when the thread is enabled and 4 (:1>17 is used, it takes 2 minutes to calculate the bit correlation (one quarter of the original). Meta-agglomeration When several bits are fully correlated (ie, 'always all or all i'), they can be coalesced into only one bit without releasing any information. Will be in a given zone The set of fully related bits is called a "group", and the bit vector of a given area is composed of several groups. If the bit vector of N bits is composed of n groups, the bit of N bits is encoded. The metavector uses n bits + a small table to indicate which bits in each region are equal. This bit coalescing has the advantage of reducing the size of the resulting file in a lossless manner. It may increase as the number of zones increases, as more bits may be coalesced. So the map size increases in an owual, linear manner with the number of zones. In one embodiment, the following information is obtained:

Minimum number of groups 255 districts in the Netherlands, Belgium and Luxembourg 12_ 13 300 districts in the Netherlands, Belgium and Luxembourg, the average number of groups 84 90.017 150831.doc -84- 201211509

There are even fewer groups after the Fuman encoding). The area of the 255-bit bit vector (also)) (and therefore, in Huo

It takes 152 bits (152 groups). 'IJ 久久盟秫Z :) :) The appropriate area, the zone with the worst area needs to be another example before the Huffman coding and the zone Id= in the example of the Netherlands, Belgium and Luxembourg of the above 2S5 zones 3 is an example, which has the following 18 groups obtained from the encoded data. Zone Id=[3] has [18] groups: #1 (0) #1 (1) #2(2) #141 ( 3 4 5 7 1 1 12 15 16 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 36 37 38 39 40 42 43 44 45 46 50 51 59 60 62 63 66 67 69 71 72 73 74 : 75 76 80 81 82 83 84 86 88 89 90 95 96 97 98 100 101 102 103 104 105 106 108 110 112 113 119 136 139 142 143 147 148: 149 150 151 154 155 156 157 159 160 165 166 167 171 172 173 174 176 177 178 179 181 182 183 190 192 200 203 205 207 210 21 1 212 213 214 215 218: 219 220 221 222 226 227 229 235 237 241 242 243 244 245 247 249 250 252 ) #1(6) #1(9) #1(10) #30 ( 13 14 35 48 49 57 68 85 93 109 1 15 1 17 1 18 128 131 134 138 153 158 164 169 187 189 195 209 217 224 238 239 ) #59 ( 17 18 47 53 54 56 65 91 92 99 107 114 1 16 121 124 125 126 150831 .doc -85-201211509 132 137 140 141 144 145 146 152 161 162 163 170 175 180 184 185 186 191 193 194: 196 198 199 201 202 204 206 208 216 223 225 228 230 231 232 233 234 236 240 246 251 ) # 1 ( 34 ) #5 ( 41 78 79 111 197 ) #3 ( 52 77 8 7) #1 ( 55 ) #3 ( 58 61 94 ) #1 ( 64 ) #1 ( 70 ) #1 ( 122 ) #1 ( 188 ) Each line represents a group (18 groups of area Id=3) group). The number in parentheses is the index of the bits that are coalesced in each group. The number after # is the number of bits in each group. In this example, 1 group is extremely large and contains up to 141 zones. This is unusual. In general, the area on the edge of the map clusters more bits than the area in the middle of the map. In this example, the number of bits has been reduced by an average of ~1/3 (~= 25 5/84). Of course, it does not mean that the map size is reduced to the original I/] because the remaining bits to be encoded have more entropy than the original bits (so it is more difficult to encode by Huffman blocks). However, the bit coalescing bit can still reduce the map size (possibly reducing the map size). When the bits in each zone are coalesced, the bit vector in each zone therefore has a different number of bits (but the bit vector of the given origin zone has the same destination bit), as in Figure 12 Explained. The shadow says the origin (10). The y-axis represents the sequential order of the segments. For example, a block may indicate a called line. 'The next block may represent 5〇7 lines 150831.doc -86 - £201211509 and so on. Once calculated, 屮矣ήΑ Aw _ metacorrelation identifies the group of fully related bits & 4 ,, and is fairly easy and fast. In the case where the 01 or 10 type can not be found, the ancient & _ jin has a pair of pairs which are completely related and can be coalesced into 1 bit. in order to,,. Another example of out-of-bit coalescence, the following table gives an example of a 6-bit vector (the parent-bit vector has 15 bits). These bit vectors have not yet been coalesced. Leoiiiiaimics COQOeilOiiKJios iSil#€liiC!©i5ii.u illilQ'SliieQI.Qii 3. ^iiQSQ-ummmu

Odoec 01011251103⁄4 These 15-bit bit vectors can be grouped into only 4 groups—so there are 4 bits per bit vector before Huffman coding. This is shown in the table below: < 1 + 3 +5 2 + 11 ' '5 + 7 ^ + 8 + 10- ] 0 1 —Ί— 0 0 1 i-- 0 1 〇— 1 1 0 0 1 0 — 1)--- 0 0 Ί ~~ -

The title of the right part of the table shows which bit in the left part of the table constitutes a 4-bit coalescing vector. For the sake of clarity, the first bit of the 4-bit coalescing vector represents the first, third, and ninth blocks of the left portion. Therefore, since the second part (ie, the 15-bit original vector) of the above example is the 150831.doc-87. 201211509 bit, the 3rd bit, and the 9th bit are always the same, it can be obtained from the above table. The first column on the right side is indicated. Therefore, the table of consistency between the left side and the right side is as follows: The original bit coalescing bit 0 0 1 1 2 1 3 0 4 0 5 3 6 2 7 1 8 2 9 2 10 3 11 0 12 3 13 1 14 1 The coalescing bit effectively groups nearby destinations and destination areas in the same angular sector from the originating zone, as illustrated in Figure 13. The shading in Figure 13 refers to the group of zones that are not coalesced together. The two maps (i.e., 'Fig. 13a and Fig. 13b) show the same area clustered from the two different origin regions: the entry and the 3 perspective. Which zones are clustered together depends on the zone ID of the originating node as shown by the figure. In this figure, eight zones are clustered into four clusters. The coalescing bits are different from the viewpoint of the originating area A or the originating area B in the figures. Notice how the vertical strips (1300) are coalesced because they are in the same direction when viewed from the beginning of the 150831.doc •88·201211509 area A. This is further illustrated by Figure 14, which illustrates the coalescing bins grouping nearby regions of interest and destination regions in the +/_ same angular sector from the perspective of each originating region. The number of bits to be encoded in the bit vector of each zone after the coalescing bit: the same. In the case of, for example, the 255 districts of the Netherlands 'Belgium and Luxembourg, the number of bits of the bit vector for each zone is: originating zone -> agglomerated bit 1 ~> 57 2 -> 93 3 ~> 18 4 -> 12 5 -> 63 6 -> 75 •...shear ·.. 251 -> 21 252 -> 46 253 -> 117 254 -> 80 This method is Accurate (it is not trial and error). Therefore, it finds the ideal number of groups of bits. In a case, the coalesced bits are implemented in a lossless manner: the regions are only coalesced when they always have the same bit. In other embodiments, however, this can be extended to cause loss of coalescence bits; that is, it is impossible to fully recover the original data. Such lossy embodiments may introduce a threshold (ie, 'near measure'): if the difference between a pair of bits is less than X times, then in the bit 疋 in the "some bits of the vector, replace one or In the case where multiple 〇 allow their bit vectors to be coalesced, the equal bits can be coalesced. Because of A, in some embodiments, substantially related bits perform this coalescence. An example of this lossy water junction would be to coalesce 〇〇〇〇〇〇1 1(9) with (9)(9)(9)1 1 1〇150831.doc -89- 201211509. One advantage of this approach is that the data is better compressed, but the disadvantage is that the path selection method using the bit vector will evaluate the other road segments because the extra 1 will indicate that a road segment is part of the fastest route. In the case of no loss coalescence, the threshold is 〇. Increasing this threshold will allow coalescing other zones at the cost of introducing a few bits into the bit orientation. However, if the threshold is kept low, it will have little effect on the speed at which path selection can be performed using this data format. For example, if two bits in the thousands of bits are almost always the same (except for, for example, only J bit vectors "outside), then the difference in this unique bit vector is changed to make it possible Aggregating more bits may be acceptable. The higher the threshold, the more map compression is expected. Bit Reordering In the t-plus case, if the bit has been coalesced (as described above), the bits can be reordered. Reordering bits does not reduce the number of bits to be encoded (before Huffman coding), but helps to make Huffman coding more efficient '#and reduces the size of the map' and can also help The number of distinct codes in the bit vector Huffman code is reduced, thereby reducing the memory requirements of the Huffman tree. Unlike bit coalescing, bit reordering is a trial and error method so it can find a good reordering' but it may not find the best reordering. The bit vector is encoded by block. The block size is customizable and is stored in the icon header 800. In the explanation given below, and as an example, the block size is set to n bits. The number of bits in the bit vector " 150831.doc •90· 201211509 can not be divided by 11, so the last block may be less than 11 bits. The last block uses a different Huffman tree than the Huffman tree used for the complete block of 11 bits. The encoding per bit vector is therefore encoded: • Uses several complete blocks of Huffman code for an 11-bit block (in this example) • Use another Hough when the remaining bits are less than 11 The last block of the Manchester code. The following picture depicts the bits to be Huffman-encoded by block, where the bit vector 'in 2 regions (which have a different number of bits after coalescing): <complete block>< Complete block > last block

<----Complete block----><----Completeblock-><----Completeblock----> Each area Having a Huffman tree will most likely be too costly in terms of memory. So in some embodiments, all zones share the same Huffman tree. Since the associated bits are different in each zone, it is advantageous to reorder the bits in each zone so that the associated bits are systematically placed at the same location in all zones. So sharing Huffman trees across all zones becomes more efficient. 150831.doc -91 - 201211509 The table that will be used to reorder the bits and numbers of each zone and place 70 is stored in the map data. Note that there is no need to code a separate table for the public and a table to reorder the bits, but instead encode only! A table, which is a composite of two (four) (poly # + ί (four) orders) (eQmpGsiti〇nb reorders the bits in the complete block as follows) For each-zone, find the most relevant bit Yuan. Since the complete _ bits have been coalesced, the remaining bits are not completely related, and some bits are much more relevant than other bits. Remap the most relevant bit pairs (a, b) to bits #〇 and #1 :

/ The most relevant bit pair in the group, so the Huffman tree of the complete block has fewer dissimilar codes (this has the advantage of using the car to store less memory to store data), and the statistics are more skewed ( Make Huffman coding more efficient). In the vast majority of cases, the first 2 bits (for example) contain (9) or 丨丨, but almost never contain random bits, the first 2 bits will contain no 10 or 01 (other bits are also So), the sequence. In the case where the bits are not reordered, various patterns 01, 01, 1〇, n are used. After remapping the first 2 bits, the method then finds the next most relevant (c, d) bit pair' and remaps it to store it in the 2 bits before the second block:

Next, the method again finds the next most relevant (e, f) bit pair and weighs 150831.doc

S •92· 201211509 Newly maps it to store it in 2 bits before the third block:

When the last complete block is reached, the method returns to the first complete block and remaps the next most relevant bit pair (g, h). If several pairs have the same correlation, the tie breaker selects the pair that is most relevant to the previous pair in the same block (ie, the pair most relevant to (a, b)): ! abgh , . . . . .led.........| e f.........| >t κ x | Algorithm approach continues as described above until all bit pairs in the complete block Has been remapped: |ab ghmnstyz . jcdij ο ρ υ v AB . | efk I qrv; x CD . | x >: x | In this example, the block size has an odd number of bits (11 bits) ), so there are still unmapped bits in each complete block. The method then finds the bit most relevant to "Z" and stores it in the first block. Then find the bit most relevant to B and store it in the second block, and so on, until all the complete blocks are remapped: +.«» as: wra».os ass sk s«.Ka3K· .»»:«·«»swwsksskterra's»-f «KWKWiKsas wasesssssa:«β.τκ a* s«.rs:»B..;!2r.»»sa.sK. +sa.ss. ssss·?» «κ ssaaas «saasssssraa «sas; etees-aa es 4------+ I abghm n. styz EI cdijopuv ABF | efh I qi: wx CD G1 κ xx | . At this point, all bits in the complete block The meta is remapped. The method then remaps the bits in the last block, attempting to group the most relevant bit pairs (as done for the full block). Reordering the bits in the last block can help reduce the map size, but it is not as helpful as reordering the bits in the full block for two reasons: 150831.doc - 93 - 201211509 • The complete block is more important. In this example, each code uses 3 Huffman codes for the complete block, and it uses only 1 Huffman code for the last block, so the complete block is the last incomplete last block pair. The contribution of the total map size is greater as normal, and it is more useful to optimize the Huffman coding of the complete block. • Since all the most relevant bits in the complete block have been picked to remap them, the remaining bits to be remapped in the last block are less relevant. Therefore, the entropy of the bit in the last block is therefore higher than the entropy of the bit in the complete block. In other words, the Huffman coding of the last block is not as efficient as the Huffman coding of the complete block.

Should be § live, use the same Huffman tree for all complete blocks in all zones. In the above example, the bit vector is encoded so that all the complete blocks are encoded with the same Huffman code, and finally the last block is encoded with a different Huffman code: • ssa a® as moldy torment; Dare to build + ^t>ghmnstyzE| (using 3 complete blocks of the same Huffman code) | cdij〇pUVABF|

lefklqrwxCDGI ~r rssa ss jail as in «5Γ·! π rsrB; + — — — + (using the last block of another Huffman code) When seeing the above figure, the method remaps each zone The reason for the first bit of the block (rather than re-mapping all the bits in the first block before jumping to the second block) should be clearer. Since the same 15083I.doc -94- 201211509 code is used for all complete blocks, it is necessary to make all the codes of all blocks as identical as possible. If you remap all the bits in the block, then remap all the bits in the second block (and so on), then each block will have a very different pattern: the first block will have the most The associated bit ^, the second block will have less relevant bits, the third block will have more unrelated bits, and so on. It will be possible to generate several Huffman codes for each line of the complete block, but it is believed that the cost of memory is too high. The method outlined so far works well while making all the complete blocks share the Huffman code. Possible other optimizations to further compress the data This section describes the optimizations that can be used in other embodiments. Page Page Page Information Storage - Difference Block, which is used to (4) start offset per m vector page. Use the linear interpolator of offset (linear) to store the differential slits. However, the material offset is not linear, because the bit vector around the small node m (level 〇, highway) is higher than the high _ (level $, The bit vector around the destination road) requires more bits. The graph in Figure 15 does not show the difference between the maps of the Netherlands and the map of Belgium and Luxembourg. The encoding of the bit TL vector page information is not as expected. The ground is advantageous because the inner = cannot accurately predict the actual offset. By modifying the interpolator, there will be a code that can improve the vector page information table to make it more efficient. An embodiment may use a bit TL vector page (and possibly a page page) having 2 levels instead of only 1 level. A page with 2 nodes for grouping data 150831.doc -95 - 201211509 may be used. (referred to as subpages) are grouped into pages with 2N subpages. Thus 'linear interpolation parameters will be stored by page rather than globally (in the header). For example, t's bow 1 level 2 may be 24 = 16 nodes are grouped in subpages, and index i can *2i〇 :=1〇23 subpages are grouped in the page. The receiver is for 1〇24x16=16K nodes instead of counting all nodes (50 in the maps of Europe and Russia, 〇〇(), delete nodes Linear interpolation occurs so linear interpolation for variable size offsets becomes much more accurate and the difference in index 2 is therefore smaller. In the case of large pages, extra index! $士,& , , d α only • Le W丄 is small in size (small enough to fit into the memory). It can be loaded with a dream of T; J clothing is sorrowful, it is beneficial, because it should not Slow down the path selection using this data. You can then store the average page size for each entry in the index i table instead of storing the average page size in the header. There are 2ΛΝ subpages with 2Λn nodes index 1 page Index 2 subpage +------+ ........> ------------ 1 I Page 〇丨----->+__________ + -------+·.·.+ -----------

I I · 1 1 丨 | 2Λη originating I + --------- Node variable | !______| 'Page 2 ! , size data |

Ten·10** ~ -I _ ten ------------ τ.*—one _ — — one + I page 256 | --------- I Page 257 | + One-to-one.—. -4- s 150831.doc •96· 201211509 The parent misplaced vector page describes the interpolated path of page offsets (many non-trivial 旌pm D is inaccurate because important The VT eve and the tenth flag) and the secondary road vector are different in the position of the Π ή ή σ 平 平 旗 旗 flag. The pages of the network level that make the interpolator more linear are interlaced, and this can be too private: the early mode is used to make different and different examples. The files described in the above embodiment are stored on the following page. #0只. #1 #2 #3 §4 ππ -3 #.η-2 frri -1 It is possible to store in a staggered manner in other implementations that may be more effective. The example is as follows: #〇

#nI #1 #π —2 #2 # π-3 #3 #η-4 To access page #χ (for example, by the route planning application), access the page by loading page #x', where : • Χ' = 2χχ (where X is an even number) • x' = 2x(x-(nl)) (where X is an odd number) This embodiment should be advantageous because it will reduce the size of the index by a few per page Bit. However, the data may be poorly grouped for the cache, this 150831.doc •97- 201211509

Monthly data access can be slowed down (less hits in file system cache memory). Do not store the zone IDs of all nodes *Do not store the node ID of the node with no exit and the zone ID of the node with 2 attached road segments. For path selection, these nodes can be ignored. Entering one of these points can be converted into entering its neighbor decision node. Store additional information at the page level and/or node level. View map data. There are many vector pages that contain only the ordinary bit vector 000.·._ or 11 ι.._ιιι. Some embodiments may store 1 bit for each page to mark their pages, then storing the bit vector in those pages may be more efficient because only a single bit is required for each bit vector to indicate Is _.,._ or "L·(1). Not only will it reduce the size of the page containing only the ordinary bit 兀 vector, but it will also better optimize the Huffman tree with the non-trivial bit vector, the bit vector code of the page (because they are better) The code, the frequency will increase significantly in percentage, so the number of bits used to indicate non-trivial to S will decrease). In finer network levels (e.g., level 3), most pages contain only trivial bit vectors, so there may be only one bit vector per page in about half of the pages. Storing only the bit vector at the decision node As discussed above, some embodiments may not store the bit vector of a node with W attached road segments. However, other embodiments may be more proactive and extend the idea to storing only the bit vector around the decision node. Introduce the concept of decision nodes and decision road segments, as it can be advantageous in programs that encode map data: there is no need to code non-decision road segments

S 150831.doc -98- 201211509 Metavector, as discussed now. • The decision node is _ 筋# . That is, the point where there is a road segment for the path selection, you > day a causes the 仵 to leave the node (without multiple choices. 4) The non-decision node is not the decision node node. So regardless of the path, the choice from the rationale 'always only exists' - the way to leave the node. The decision road segment is the legal road segment used to leave the decision node. • Non-decision road segments are road segments that are not decision road segments. Jin has a road section that is therefore around the decision node. But all the road sections around the point are, ^^, gt; white is the road section of the deterrent. All road segments around non-decision nodes are non-decision road segments. Only the bit vector of the decision road segment will be encoded. The non-decision road segment is implicit in the summer or (1)·.."", because the use of this information: plant selection technology can be determined based on the information already existing in the road segment. How to determine whether a node is Decision node? The criteria can be reduced to: isDecisionNode^HneCount^) && (lineGoi„g〇utC〇unt >^2) where: the total number of lines of the line (railway, reference lineCount. attached to The node line ignores the path selection path that is not possible, and ignores the closed circuit in both directions and ignores the prohibited road (residential area). 150831.doc •99· 201211509 lineGoingOutCount : The number of lines that are attached to the node that can be legally selected for leaving the node. Select a road segment to leave the node as a legal sight segment attribute: • Road segment type (railway and reference lines are always illegal) • Road forward/backward flow (stored in the road segment flag) • Prohibited Passage Attributes in Road Segment Flags (No Pass Road Segments Do Not Have Any Bit Vectors) In some embodiments, a non-decision road segment may be discarded to discard approximately 4% of the road segments. The ' & percentages have been found to be fairly consistent and not related to the map. Avoid coding 40 /. The bit vector is advantageous, but it saves less than the map size because it primarily removes the trivial bit vector. Removing a bit vector around a node (dummy node) with less than 3 attached road segments removes the non-trivial bit vector, so the map size savings for non-decision road segments of this category are comparable to for non-decision road segments The map size is large. The other party φ, the filter requires a decoder (such as using the path selection method of the map) to decode the road segment type and the road segment flag of the line and apply logic to it to clarify the implied bit vector, which can slow down the program. . The _ upper shell example can also view the movement (ie, the turn limit) to determine if the exiting road segment is legal, but this technique adds complexity. Ignoring motion means that the embodiment may encode more than the strictly necessary bit vector: the meta-vector, but the simplification of the method is achieved. Non-decision node instance

S 150831.doc .100- 201211509 In this example, '(b) is attached to two road segments that can pass in both directions. (b) Not a decision point because there are <= 2 attached road segments. Therefore, the bit vector of the two road segments leaving node (b) will not be encoded. The decoder can implicitly set it to 丨丨丨丨丨1. δ >--b—<->—^ d The arrow in this example shows the legal flow direction. (9) Not for decision-making Because there is only one-out σ. Therefore, (b) all road segments around do not require a bit vector. The bit of the road segment (b)_>(c) that leaves the node (8) is not coded = the cell 1.1·111. Nor does it encode the bits of the illegal road segment leaving (b) to I ’ which will be implicitly 〇〇〇 〇〇〇. Example of a decision node f

I d (b) is the decision node because when it comes from (d), the save option can continue toward (a) or toward (c). Sub--Select: Path Note that in this example, when from (a) no... can only continue towards (c). But node (b) is still black for decision making, and path selection is at least one choice from (4)' so it should be stored... because (4) two 150831.doc -101 - 201211509 decision road segments around the point . The bit vector of the road segment (b)-> (a) and the road segment (b)-> (a) is stored because it is a decision road segment. The bit vector of road segment (b) -> (d) is not stored because it is illegal to select this road segment based on the forward/forward flow of traffic. It is implicitly 000...000 ° logically for the bit vector or assumes that the node has 3 attached road segments, and the first 2 decoded road segments have the following bit vector: 00000000000000000000 〇〇〇〇〇〇〇〇第The third bit vector does not need to be encoded, as it can only be: 1111II11111111111111 This only works when the bit vector of the road segment around the node happens to be in this order. : All bit vectors are 〇〇〇..〇〇〇 and the last bit vector is 1 11...111. In practice, it appears that it occurs quite frequently in a finer level (e.g., level 3) network (which is where most road segments are located). The first 2 bit vectors are taken as: 00000000000000000110 00000000000000000010 All bits of the third bit vector can only be set to 1 except for 2 bits that are unknown and need to be encoded in some way. 11111111111111111??! Since most of the bits are known in the above example, it should be possible to encode the 2 unknown bits 150831.doc -102-201211509 more efficiently using this lean ratio encoding the entire bit vector. Therefore, in this example, only 2 bits must be encoded. A possible fast scheme using this property would be to compute the position of all decoded bit vectors of the current node's road 以 by logically ORing the bit vector that is good for the road segment. In the case of using the same example as the previous example, if the node has 3 attached road segments, and if the previous 2 road segments have the following bits 〇 0000000〇〇〇〇〇〇〇〇〇11〇^ 〇 〇〇〇〇〇〇〇〇.〇〇〇〇〇〇〇〇〇1〇...The logical or bit mask is: 00000000000000000110 The third and last bit vector to be encoded around the node is taken as: As long as the following conditions are met, the encoder can freely encode any other code (otherCode) instead of encoding the 11111111111111111〇〇1 Huffman code (which can be rare): v/alu.e_to_encode =~bitEask j otherCode ο In this example, '〇therCode = 000000〇〇〇〇〇〇〇*〇〇〇〇〇〇〇 meets the requirements because: ^ - 11ϋ11ιΐ1ΐιιχιι110ί}1 ^ -ίί〇ϋ00ϋ000ϋ0ϋ〇*〇ϋ〇〇ιι〇| ϋ^υ〇〇0^υϋϋ〇ϋ〇>〇〇υϋ0ϋϋ The code 〇〇〇〇〇〇〇〇〇〇〇000000000 is much more efficient than the code 11111111111111111〇〇1 because 〇〇〇〇〇〇〇〇〇 Frequency To many. Decoding to fast 'because decoding only needs to calculate the bit mask (logical OR) whenever it decodes the bit vector and apply the bit mask to the last decoded bit vector: 150831.doc •103 - 201211509 Actual bit vector = bit mask & decoded bit vector = -000000000000000()()] 1() & 〇〇()〇〇〇〇〇〇〇〇〇〇()〇〇 〇〇〇〇=1Μ1ΠΠΜ1Μ1111001 This optimization works well in the case where the road segment around the node is stored such that a road segment having a maximum of 1 in the bit vector is at the end zone. However, this can prove to be difficult: • Perform a classification of the road segments around the nodes before calculating the bit vector (unless it is re-encoded using the bit vector information by the fruit and the ground (a p0steri〇ri)) The road name classifies the road segment. It is possible to classify road segments around a node when the road name is identified. Use network level In addition to the level of these areas, the road segments within the map data are sorted according to the road segment level. There should be a strong correlation between the bit vector around the originating node and the road segment network level: the path selected to another zone will typically prefer to select a graded road segment network', e.g., a highway or the like. The most important road segment network level may be the highway level, which can be used to describe the road segment with different network levels and the I line (2)->(1) at the network 4 (important) ) I line (2)->(3) at network 5 (secondary) The bit pattern is likely to be as follows:

S 150831.doc -104- 201211509 2 1 ????????*?·?,, 2 3 ???????????? 3 4 〇〇〇〇〇〇〇〇〇〇位 位 〇〇 〇〇 〇〇 〇〇 〇〇 〇〇 〇〇 〇〇 〇〇 〇〇 〇〇 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位 位). Therefore, it is possible that the bit vector at level 5 is not stored, and therefore, the influence on the path selection should be minimal (even if the number of road segments at level 5 is large). In most cases, the path selection will only explore a few road segments at the least important network level at the beginning or end of the route, as it will quickly reach some of the more important road segment network levels, and The search acceleration data about their nodes will almost always tell the router to skip back to the least important network level navigation segment and use to or continue to stay at the more important network level. Navigation segment. This is established at the most important network level 'because the network level is used when the destination is still far away. In addition to discarding the bit vector at the least important road segment (e.g., level 5), the zone ID at the network may not be encoded. Converting a few 〇 in a bit vector to 1 is also a lossy compression scheme. If the bit vector contains only one 〇 (or possibly, less than - small margin), then it may be possible to convert it to 1 if the following result is produced (ie, set the road segment to Part of the fastest route): • Trivial bit vector 111...1 1 1 (because the trivial bit vector is encoded in a compactr way than encoding non-trivial bit vectors) 150831.doc -105· 201211509 or already in the current bit The bit vector found in the history of the vector page (because their bit vector is also encoded more efficiently) Converting the bit to 0 in 昼 does not affect the path selection result, it only considers the path selection More road segments (because they are now set as part of the fastest route) make the path selection slower. However, the second embodiment of the present invention can use this method - especially if the map savings are large while the perf0 rmance hit in the path selection speed is small. Path Selection Figure 15 shows that the map 16 〇〇 丨 covers an area and has a start node 1602 and a destination node 16 〇 4 and a plurality of road segments that have been explored by the prior art eight* search method. The selected route is shown by the dashed line 16〇6. Figure 16 shows a map 1650 that covers the same area as the map of Figure 15 and also shows the same start node 16〇2 and destination node 16〇4. The figure also highlights the roads explored using embodiments of the present invention that utilize the same road network and the same criteria as those used to generate the route of Figure 15 (e.g., both travel by car, hopefully speed Used as a cost function to be minimized, etc.) The route selected by the method is again shown by dashed line 16〇6, and it should be noted that the line is the same as the line calculated in FIG. Thus, it should be noted that the route calculated by embodiments of the present invention can be so-called mathematically accurate and can find the best/best route for a given cost model that has been selected to be minimized. Accordingly, it should be apparent that the road segments explored by embodiments of the present invention are significantly less when compared to prior art. Thus, in contrast to prior art V methods, the method of the present invention, £ I50831.doc -106 - 201211509, is relatively rapid and generally significantly faster. It should also be 'thinking' that as the route 16〇6 approaches the destination 1604, the 'Eight-night route is explored compared to the beginning; that is, when the route 16〇6 advances past the point 丨652, explores the route except for the lowest cost route. path of. One explanation for this is that the method has switched from the level zone to the level 1 zone at point 652. As should be seen, other road segments are explored near destination 1604. Once again, this situation can be explained by switching from the level to the level 2 by means of attention and line planning methods. Therefore, when making a long-range path selection, $ will often only have one fastest route. & and as the method switches to a finer level (e.g., from level 〇 to 1), there may be more than one route marked as "lowest cost" and therefore need to be searched. Can be used to calculate the route between two points. Figure Π shows the previous technique of exploring the network by the route planning application. The method is to make a decision on the road segment. To achieve this, the cost of traveling to the next node is added to the estimated cost of moving from the eccle-lang point to the target. Then proceed to explore the path from the given node: the path with the least cost. The method maintains the sum of the costs incurred as the method proceeds: and considers the smallest example in each-reverse, and §, and estimates the distance B (starting node) at node B from two cost single node Fs. The cost starts at 3 units, and it can be seen that both nodes C and D are in position. However, since node D, arrives, and from node C, the estimated cost of reaching 15083l.doc -107· 201211509 of node F is 5 units. Therefore, the A* method will explore the route to the node D more preferentially than the route to the node C, because the estimated cost of adding the cost to the target for the node DC road & Small (ie, BC=2+5 = 7, and BD = 2 + 3 = 5). When considering the use of the bit vector of the embodiment of the present invention to perform the route planning day ^per-road segment bit (i.e., the column of Figure 7, identifying which road segments are candidates for the lowest cost route to the destination area) Thus, the A* method described with respect to Figure 17 is modified to the one shown in Figure 18. The route planning is typically performed using a bit vector, as described with respect to Figure 18. However, some embodiments of the present invention may allow Route planning is returned to (or other prior art methods) in various situations. Different embodiments may utilize any of the following: missing bit vector information ( thereby allowing the system to even have a bit vector in place) The case works; use the cost function; except for the path selection for which the cost function of the bit vector is calculated (usually the fastest route, but not necessarily); the user specifies and uses the pre-computed bit vector They have different criteria (the case, the user wants to avoid the highway); the type of transport is different from the type of transport used to pre-calculate the position of the 7C For example, 'the user walks and does not take the car'; and the route is below the threshold length (for example, the start and end points of the route are in the same zone). Compared with Figure 17, 'two additional numbers are shown in Figure 18, ΐ8 〇ι. In addition, the areas are indicated by dashed lines (10) and deleted on the figure. The surface indication road segment BD is part of a low-cost route from the node to the area where the target node is located (as described elsewhere, it may be additionally There are other 150831.doc 201211509 low cost routes.) "〇" just indicates that the road segment BC is not part of any low cost route from the node B to the zone in which the target node is located. Thus, when starting from node A, the invention The embodiment will use the A* outlined above to explore the node from a. Then, once Node B' has been reached, there is no need to use the exploration further because there is only a road segment BD that is a possible part of the lowest cost route. Clearly marked. Thus, once the A* method has been used and the lowest cost route is found, it will then select the lowest cost route by looking at the relevant bits within the bit vector. Time has a different minimum cost path between a pair of zones' then the minimum cost data can identify more than one minimum cost path between the pair of zones. Therefore, the path between the starting node and the target node (starting point and destination) The choice may find more than one minimum cost path and must choose between competing minimum cost paths, such as the number 1800 in road segment 61) and the number 18 〇1 in road segment BC have indications that each road segment is at a particular time In the case of the value of the part of the minimum cost path "丨". In this embodiment, the bit vector does not identify the time at which each road segment is part of the least cost control. Thus, the path selection algorithm implements a cost analysis of the two possible least cost paths based on the time traveled over the segment of the path. This time can be determined based on the departure time from the start/start node. The velocity profile is associated with each segment (as shown in Figure 〇a), which is a function of how the expected speed of travel through the segment changes over time. Based on these speed profiles, the expected speed at the relevant time can be determined, and this can be used to determine the cost of traveling along the road segment at that time. By the cost of the hinge along the road segment of each of the least cost paths, the cost of each minimum cost path can be determined 150831.doc -109 - 201211509 The navigation device can then select the least cost path with the lowest cost at that time. As a route. To perform the path selection described so far, the bit vector information is obtained from the encoded side file described with respect to Figures 8 through 1 using a decoding procedure. The output of the pre-processing described above includes: • Hierarchical zone assignments for most nodes, and • Pixel vector assignments for outbound road segments at these nodes. Map loading consistency check When loading map data, 'the collection of side files should be presented in the ground_ otherwise', otherwise 'decoding H will cancel the search acceleration data, so that there is no search acceleration data. Throughout the route skills. There are several checks that help to confirm the integrity of the Becco, and these checks are now listed. Side files follow a naming convention. Two =; given by: the number 8 of the building, but the number of grades is also stored in the header of the side file and equal to the number of side files. Each side (4) has its own (four) level. The name of the Zhao Shishi π double 指定 is the same as that of the side 。. In addition, the sidecast case (which should be the same for all side files): Save the information • Side file version. The number of nodes for each 70-way page (explained below). There is also a sum check code in the parent side file that identifies • a specific entire side file set 150831.doc 201211509 • The entire map. This information should be correct for the associated side file of a given electronic map. If any of the above checks fail, the search acceleration profile will not be initiated for this map. Data Structure Loaded into Memory The decoder reads the side file in the external memory implementation. This means that the contents of the bit vector side file are not completely loaded into the memory, but are read only as needed. However, at the beginning, some of the general data is loaded into the memory, and as long as the map is loaded, the data is retained therein. Header Information Each side of the file begins with a header section containing the information described above with respect to Figures 8-10. This information for each-side project is stored in memory. Huffman Tree Definitions Side files contain definitions of several Huffman trees. The per-Huffman tree definition gives a complete description of the special U-f code, and is later used to decode the side-floor case...-part into the original data (ie, decode the 仏 sequence from the side-mark) In-number or some other specific value). The following Huffman tree definitions are read from each side file and are taken into memory. • A Huffman tree used to decode the number of road segments at each node. (The number of encoded road segments can be smaller than the number of road segments in the base map. Note that the decoder is independent of the base map, ie it does not need to read the map). This Hoffman tree is only stored in the file on the side of the level. 15083l.doc -111 - 201211509 The Hoffman tree on the page of exhaustion (explained below). A number of Huffman trees used to decode a bit vector block. The number of tree definitions is given by the length of the rule bit vector area in the header of the case (4), which is equal to the block length minus one. (The entire bit string of the _ inward of the road segment is split into blocks. If the length of the bit vector is not a multiple of the regular block length, then the last region: the bundle is shorter. For the length from 2 until the regular block Each block length 'exists - a Huffman tree. The Huffman tree is not used for long blocks, because this is only one bit and is stored directly). Several Huffman trees for selecting the decoding method of the bit TL vector. Specify the number of such trees in the ^ header; explain their use below. The list of neighbors, the most refined, the level of the mother of the Tianji class, the side file encoding the neighborhood list level k, the neighbors of the district clearing zero or more than the level of the neighbors of the level ^ zone (k+i ) A list of districts. The neighbor list of the side file of level k has two parts. The first part contains the number of neighbors of each level k sub-area. For example, s (k=l) 'If there are 4 areas in the global level, and each whole area is subdivided into 1 level 1 area, then the level 1 side file contains 4000x10 levels 1 Area. The length of the individual neighbor list (which consists of level 2 regions) is given for each of these sub-zones. • The second part contains a list of actual neighbors, 纟 each S degree from the first

S 150831.doc -112- 201211509 The number of each neighbor list is a list of level (k+1) sub-areas. Therefore, the 'neighbor list' specifies the area within the visibility area of the destination area for a given destination area. Thus, an indicator is provided for identifying the extent of the visibility area to the navigation device using the map material. Thus, the route plan using the search acceleration data can identify whether other search acceleration data is available to the destination area, which can be used to constrain the explored navigable segments, thereby speeding up route planning. The area remapping table side file (for example) stores the bit vector in a compressed format by coalescing and reordering and the like. The side file at level 1^ has a zone remapping table for decompressing the bit vector encoded by the block. It consists of two parts. The first part is an array indexed by level k sub-areas. For each sub-region at level k, it contains the length of the compressed bit vector. This is relevant for the outgoing road segments of the nodes of the respective sub-regions of the block-coded bit vector. • The second part is a two-dimensional array indexed by (1) the bit position in the uncompressed bit vector and (2) the level k sub-area. The array entry specifies the uncompressed bit $ read by the block to the position of the location of the location element in the compressed bit vector order. Note that only the first part is held in the memory; the second part is used as needed because it is large. Currently, the storage area remapping table is only available at the full file (k=〇). Start route query The decoder is used to speed the route from the departure position to the destination node set. 15083I.doc •113- 201211509 Search the entire road or multiple targets. (An instance where a destination consists of more than one node is the case where the link is used as a destination). The destination node defines a collection of zones. Note that the target area is a sequence of area IDs, and each division level has one (four) (: starting at level 0). At the beginning of each-new search, a set of eyeports is established by clearing the previous set and passing the new destination node to the decoder. The decoder will determine a list of target areas that are not duplicated. Used for: The mechanism to the zone of a given node is the same as during the search; see below for details. Scanning Node Remaining Discussion during Route Search Assume that the set b target of the set target zone is characterized by the node of the provided road network (4) returning the road segment leaving the node: the indexed bit array (this node and give The function of the bit vector of the target area: the order of the nodes and the road segments at the nodes is defined by the map. Whenever the bit value is zero, this means that the corresponding road segment can be ignored during the search. (This usually results in a large reduction in search space and therefore a significant reduction in the operational time of the search). For a few nodes, zone information or bit vector data is not stored in the side file. For these nodes, the decoder returns a bit string with all bits as 丨 (this will prevent the route search from skipping any road segments at this node). The decoder has a Boolean query function indicating whether this is the condition for a given node. In addition, there is a Boolean query function that indicates whether a given node is in one of the previously located target zones. The bit vector of the node in the target area returned by the decoder is again a bit string of all bits. These Boolean query features are used for optimization in route search. Π 4 150831.doc 201211509 According to the side file format, the bit vector data of a given node is decoded in several steps. In each side file, the zone and bit vector information is organized into so-called pages. The number of nodes per page is a fixed power of 2 (for example, 丨, and the file for each side of the set of side files is the same. This means that for a given point ID, a simple bit can be used. Shift to calculate the page index of the bit vector page. The information of the node is continuously stored by the node ID. Finding the page offset of a given node for the parent-side standard 'the average number of bytes per page is stored on the side The header of the file is used to approximate the byte offset of the page by multiplying the page (4) by the average size. The correction is stored in a table indexed by page. This table is stored. In the separate section of the side file. When querying the page, look for the correction item in the table, ride the item and add 6 hai; f parent positive item to the approximate page offset, giving the position of the page in the side file Decoding page cache, although the first time the page is queried, decodes (relative to the target area set) and caches the bit vector string of the node in the page. The cautious 蛀 soil-person self-same-page query node takes :,...Using cached data without any side file accessing the second decoded bit vector Special tag bit string based membered § Hai to remember whether or not the node information node. 〃 π p

For each page, the so-called page number bits specify 誃 yr & , all the throttlings in the title page; I no, have the same zone ID. Page number for each level contains " 乂 汾 汾 1 1 位 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , . Decoding Outbound Road Segment Count As mentioned above, each page contains information on the right ΙϊΙαα w,.., the number of nodes. This number is stored in each side of the file (or for 箄铋n. _ μ軚 中 。. At the beginning of a page 纣 to level 4 〇, after the page number, out of the road ° page lists each of the pages The number of one node (outing roads & the number of road segments that are not in the case of love, this means that the corresponding section of the festival is not stored at all - #..Beckon. When decoding the page, the number is Stored in the temporary array. The decoding area is given in the section of the section after the section of the road segment count, and each of the equals * plus "the point of the W point is the order of the & ID, 丨 0 安七疋The ID of the zone is stored in the corresponding side file. The decoder reads the page Γά 0 ^ ^ . The kilobytes are in the area of all levels. Although the information of the nodes is not stored (also in the earthquake, the sun, the Ρ - that is When the road segment count is zero, the zone tribute is empty. The solution me decodes ^ the road segment count is greater than zero, the zone ID sequence of the 卽 point is ^, and the page number of the J right 疋 grade is specified at the level. All the zone IDs are the same, &the temple phase Π F τ η I then set the phase for all nodes at the 4th level. The road segment count corresponds to the area at the level. In this program, there is a P., 』 at the end of the private sequence of the private seven, the decoder has filled the page with a complete sequence of IDs of the page. τ These sequences may find the set of relevant bit locations for the null decoding bit vector. For a given node and the target zone, the specific bit at the material level is the value of the bit vector bit of the road segment leaving the node. When there is a target area of 150831.doc -116-201211509, the resulting bits are logically ORed. For each point 'decoder, the set of related bit positions is calculated. For the parent-outbound road segment at the node, The set of related bit positions is the same. It depends only on the set of the section and the set of the target t. If there is only one target area, there will be only one relevant bit position at the -level; in other words, For this node, the information stored at other levels can be ignored. In the case of more than one target area, the positions of the relevant bits can be coincident, so there are always as many relevant bit positions as there are existing target areas. In the text, Discuss how the decoding benefit determines the relative bit position of a target zone. For more than one target zone, 'the relevant bit locations are found in the same way and the relevant bit locations are combined into one set. When the neighbor zone is not defined, for each— There is one bit vector bit per _ target area (every outgoing road segment). (For the sake of simplicity, the fact that the node itself is not (1) does not store the bit). The relevant bit is at the first level. (counting from level 0) 'The zone ID of the node at this level is different from the zone 1D of the target zone. For example, if the zone ID of the node at the global level is equal to the target zone 1D at the global domain, but the two zone IDs The difference is at level !, then the relevant bit position is at level i and it is equal to the target area. The position of the bit in the bit vector string of the (4) level at the level ^ (4) ^ skin A possible target area ID contains right - complete a - r + * has a bit 7G. The region remapping table is used to convert this position into a position in the compressed bit's string. Inward string (when the temple is actually programmed to define the neighboring area (ie, the area within the visibility area), the position is determined at the "most fine" level (in which the target area is 150831 of the node) .doc -117- 201211509 The product has four levels as an example. It is assumed that the target area is in the sequence of & b, C, and sentence, and the sequence of the node is assumed to be (e, f, g, h). If (a, b' c' d) is a neighbor of (e, f, g) (as defined in the neighbor list section), and (a, b) is a neighbor of (4), then the relevant bit is ( a, u is determined and located at level 2, that is, contains the rank of the (a, b, c, sentence (e, f, g) first code as the neighbor. More precisely, the relevant bit position is the level 2 right In the case, as the neighbor of the district (e, f, g) (a, b, c, d) (four). In this case; brother, please rule the bit h (as explained in the previous accounting) is irrelevant Again-time, this associated bit position is relative to the un-contracted bit vector string. The decoder uses the region remapping table to convert it to the bit position in the abbreviated bit string at level 2. About neighbors More information on the list is contained in the "Pr〇P〇sal for enhanced (Partitioning)" document. The decoded bit vector bits are in the case of a fixed set of given target regions. The = element vector of each node in the page will be composed of one bit per outgoing road segment. If the road segment count of the node is zero (also #, the node is no information node), then each bit will be set to f 1 is not further decoded for the other node. If the node is located in the target area, the bit vector will be all i; in this case, the encoded data may have to be skipped in order to decode the subsequent nodes. .... negative - if the bit vector of the current node is not trivial, then the decoder does determine the set of relevant bit positions, as explained earlier. Each bit position is relative to a particular level, ie The bit is located in the specific side file. In every two 150831.doc 201211509 level, the side is broadcasted to the right ^^ + 钿 system 5 has the compressed bit of the king to capture the position of the relevant bit position &; Lu 4 Ren decoding benefits only for non-use ^ During the decoding period, read (skip) the unused news (but only after it). No witness 1 gentleman * If you don't need the information, you can't buy it. The part of the meta-flow that is not used. According to the level, the position of the relevant bit is (4) the position in the abbreviated position $=2, the group. The relevant position is decompressed to read the bit position at the relevant position, the directory丨 止 + + A 丄 丄 彔 彔 彔 + + 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 丄 解码 解码 解码 解码 解码Point information. When the given side of the field is reached, the amount of the node being discussed is reached. For #夂 仃 仃 仃 向 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于 对于The information of the current section, section, and section begins with the Hoff® signature of the specified decoding method. It has one of the following values: The coward also pays to open all the bit vector bits of the road segment at this level is 〇 (packing X to pay 唬. For this road card, it is not necessary to decode other bits ^Specify all the bit vector bits of the road segment at this level as the symbol of i (all neighbor bits at this level). For this road, it is not necessary to decode other bits. • Specify the bit vector bit The string is explicitly given by the block. The solution to the compressed bit vector bit string is interpreted by ^: The bit vector bit of the = segment is placed during the encoding of the entire page. History Stacking. 150831.doc 201211509 • The illusion of the Emperor's bow to the historical stack. The symbol of the home bow. At a given index, the history stack contains the required bit vector value of the road segment. Depending on the current size of the history heap 6, a different Hough tree for the decoding method selector is used. There is a limit value for the number of specified Huffman trees in the header of the side file, and the size of the history stack exceeds this value. , then reuse the Huffman tree. Right The method selector symbol specifies that the bit vector string should be explicitly encoded, and the decoder reads the compressed bit vector bit string block by block. It collects the associated bit position at this level (relative to the compressed bit) The value of the bit at the vector string. The logical OR of the value of the bit. If the intermediate result of the logical OR becomes 1, the remaining bits 70 of all other blocks of the road segment can be skipped. The Huffman tree that decodes each block depends on the number of bits in the block. There is a Huffman tree for the length of the regular block as specified in the side file header. The last part of the road segment The block can be shorter; depending on its size, the appropriate Huffman tree is used for decoding. The block of length one is only one bit, and it is read directly without Huffman decoding. If the number of blocks At least 2, the bit stream generated from the bit vector contains an extra bit before the Huffman symbol of the block. The value specifies whether the entire decoded string is interpreted as a bitwise bit of the actual value. Yuan negation. (The purpose of this negation is better Huffman compression) Notes on Search Methods Ice S This technique should be understood by 'While the classic Dijkstra and A* search methods produce a search tree and can therefore be referred to as an example of tree search, but the general route search at a given navigable segment Usually a directed acyclic graph can be generated, which constitutes a subnet in which the network performs the search, and for any given navigable segment contained in a directed acyclic graph, There will be one or more least cost routes between the roots of the search. Therefore, when referring to a search tree or tree search, it should be understood that this concept can be generalized to a directed acyclic graph resulting from the search. Where the time varying function provides a velocity value for a navigable segment in the map, there may be more than one least cost route between a given navigable segment and the root of the search, and thus, such search uses a directed acyclic graph Not a tree search. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a schematic illustration of one exemplary portion of a Global Positioning System (GPS) that may be used by a navigation device; FIG. 1a is a schematic illustration of an electronic component of a portable navigation device (PND) or any other suitable navigation device Figure lb is a schematic diagram of the configuration of the installation and / or interface navigation device; Figure lc is a schematic representation of the architecture stack used by the navigation device of Figure la, Figure 2 is not a part of the example map generated by the embodiment of the present invention Figure 3 shows the map of Figure 2 with nodes for path selection shown; Figure 4 shows the map of Figure 2 after processing; Figure 5 shows how nodes are not assigned to the map of Figure 3 in some embodiments. Example; Figure 6 illustrates an example of how a map may be segmented into a plurality of nested regions; Figure 6a illustrates an enhancement of the segmentation of Figure 6; I50831.doc 121 201211509 Figure 7 shows an example of a bit vector utilized by an embodiment of the present invention Figure 7a illustrates how time profiled information is utilized during Dijkstra exploration of the network; Figure 8 shows an example of an archive of an embodiment of the present invention; Figure 9 shows an example of how the region remapping table and region id list of Figure 8 can be encoded; Figure 10 shows an example file format for the coarsest nested region as illustrated in Figure 6; Figure 11 shows the most Example file format of a nested area outside the coarse nested area; Figure 12 illustrates the coalescence of the bits within the encoding scheme; Figure 13 (which includes the graph na and Figure i3b) illustrates the effect of the coalesced bit; 14 also illustrates the effect of coalescing bits; Figure 15 shows a map of the route considered for highlighting prompts using prior art path selection techniques; Figure 16 shows a map of the route considered for eye-catching prompts in accordance with an embodiment of the present invention; 17 shows an example of an A-search method (prior art); Figure 18 shows a modification of Figure 17 that is not used by at least some embodiments of the present invention; and Figure 19 shows a flow chart summarizing the steps of the method. [Main component symbol description] Zone 1 £150831.doc -122- 201211509 2 Zone 3 Zone 4 Zone 5 Zone 6 Zone 7 District 8 District 9 District 15 District 21 District 24 District 27 District 28 District 37 13⁄4 41 District 42 District 43 District 51 100 Global Positioning System 102 Satellite 104 Earth 106 Global Positioning System Connection 1 108 Spread Spectrum Global Positioning System, 200 Navigation Unit 150831.doc -123- 201211509 202 Processor 204 Input Device 206 Display / Integrated Input and Display Device 208 Output Device 210 Connection 212 Output Connection 214 Memory System 216 Connection 218 Input/Output (I/O) 埠 220 Connection 222 External I/O Device 224 Antenna/Receiver/Internal GPS Receiver 226 Connection 228 埠 230 Connection 250 Dead End 252 Arm/redundant ring 254 Suction cup 280 Functional hardware component 282 Basic input/output system 284 Operating system 286 Application software 288 View generation module 300 Node 150831.doc -124- 201211509 301 Node 302 Node 304a Road segment 304b Road Segment 304c Road Segment 304d Road Segment 400 Node 600 Zone 602 Zone 604 Zone 606 Area 608 700 Leftmost Column 702 Second Column 704 Third Block 750 Node 751 Figure 752 Cost Function 754 7 56 Point 800 Ground Icon Head 802 Huffman Tree 804 Area Count/Zone Remap Table 806 Area Neighbor/Zone ID List 150831.doc -125 - 201211509 808 Area ID Remap Table 810 Bit Vector Page Index/Table 812 Bit Vector 1000 Page 1002 Node ID of the Node 1300 Vertical Strip Area 1600 Map 1602 Originating Node 1604 Destination Node 1606 Selected Route 1650 Map 1652 Point 1800 1 1801 0 1802 Dotted line 1804 Dotted line 150831.doc - 126-

Claims (1)

201211509 VII. Patent Application Range: 1 · A method for generating map data including search acceleration data, the search acceleration data being configured to increase the speed at which a route can be planned on an electronic map comprising a plurality of navigable segments, each The navigable segment represents a segment of one of the navigable routes in the area covered by the map, wherein the method comprises: a) reducing the core network by removing the navigable segment to form one of the navigable segments The number of navigable segments to be considered in the program for generating the search acceleration data; b) dividing the electronic map into a set of hierarchical regions such that the navigation segment or each navigable segment is classified into the hierarchy In at least one of each level; 1) using - a time varying function associated with at least some of the navigable segments of the core network and typically per navigable segments to determine if the navigable segment is to the region At least _l, the portion of the minimum cost route of the upper and the second v, and the determination is recorded in the search acceleration data; and d) generating the map data. 2. The method of claim </ RTI> wherein the time varying function of each substantially navigable segment is provided in part c). The method of claim 1 or claim 2, wherein the core network is generated by removing the navigable segment from which the search accelerates the lean material to be recovered later. A method of monthly term 1 or eye 2, comprising generating acceleration data for the navigable segments of the core network. 5. The method of claim 1 or claim 2, wherein the navigable segment is removed from the electronic map prior to the generating the search acceleration data according to one or more of the following criteria: 150831.doc 201211509: a navigable segment that satisfies a predetermined criterion relating to the nature of the road; the portion of the network that is formed to form the network is sufficiently small according to a predetermined criterion and can be navigated by removing a further predetermined criterion a navigable segment in which one of the segments is aggregated and disconnected from the rest of the network; in the predetermined case, the nodes appearing at the joint between the navigable segments are folded onto each other; and the shouting point has a connection to In the case of two or less of the following navigable segments, the nodes are folded onto each other. 6. A method of claim 1 or claim 2, comprising compressing the search acceleration data once the search acceleration data has been generated, the compression being according to any of the following techniques: calculating the search acceleration data The correlation of the bit pairs; the substantially related bits in the search acceleration data are aggregated in a lossless manner to reduce the number of bits to be encoded; the relevant bits in the search acceleration data are coalesced so as to Performing lossy compression; reordering the bits in the coalesced search acceleration data according to their correlation; Huffman coding the search acceleration data. • A method of generating map data comprising: search acceleration data configured to increase the speed at which a route can be planned on an electronic map, the method comprising using at least one processing device to process the inclusion complex £ J50831.doc 201211509 An electronic map of navigable segments, the plurality of navigable segments representing a segment of a navigable route in an area covered by the map, the method comprising causing the processing device to: a. process the navigable segments for production At least some of the navigable segments of the electronic map and typically the search acceleration data for each navigable segment 'is indicating whether the navigable segment is part of a least cost route; and b. processing the The generated search acceleration data is used to compress the data, wherein the compression includes any one or more of the following operations: § The correlation of the bit pairs in the acceleration data of the sigma sigma; the coalescence in a lossless manner The search accelerates the fully correlated bits in the data to reduce the number of bits to be encoded; coalescing the correlation in the search acceleration data The bit is used to perform lossy compression; the bits in the coalesced search acceleration data are reordered according to their correlation; Huffman coding is performed on the search acceleration data. 8_A method of generating map data, the map material comprising search acceleration data configured to increase a speed at which a route can be planned on an electronic map, the method comprising using at least one processing device to process the plurality of navigable segments An electronic map, the plurality of navigable segments representing a segment of a navigable route in an area covered by the map, the method comprising causing the processing device to: a. process the navigable segments for navigation by removing Segmenting to form a core network of one of the 150831.doc 201211509 navigable segments to reduce the number of navigable segments to be considered in the program that generates the search acceleration data; b. generating such for the core network Navigating at least some of the navigable segments and generally the search acceleration data for each navigable segment, which indicates that the navigable navigation # is not part of a minimum cost route; and wherein step a. includes the following operations Any one or more of: removing a navigable segment that satisfies a certain m criterion related to the nature of the road; removing from the network a portion of the network that forms part of the network a navigable segment that is sufficiently small and can be disconnected from the rest of the network by removing a set of navigable segments that satisfy some other predetermined criterion; in the pre-event, the navigable segment The nodes appearing at the junctions are folded onto each other; and in the case where the sections have two or more of the following navigable segments connected thereto, the nodes are folded onto each other. 9. A method of generating map data 'This map material includes a search acceleration package configured to increase the speed at which a route can be planned on an electronic map'. The method includes using at least one processing device to process a plurality of An electronic map of the navigation segment 'the plurality of navigable segments each having a plurality of associated nodes of the disc, representing a segment of the navigable route in the area covered by the map and having a representation associated therewith that is navigable At least one attribute of one of the parameters of the route, the method comprising: a) evaluating the at least one attribute; 150831.doc £201211509 ίο. 11. 12. 13. 14. b) dividing the electronic map into a collection of hierarchical regions So that the navigable segment or each navigable segment is classified into at least one of each of the levels, wherein the classification uses the evaluation of step a to ensure that the navigator is associated with the navigator The nodes are balanced between the zones of the electronic map; c) the map material is generated. The method of claim 9 wherein step a) and step b) are repeated until a predetermined criterion for determining the balance of the nodes between the zones is met. The method of claim 9 or claim 1, wherein the attribute comprises any one of: a type of a guideable segment; an average speed along the navigable segment; a length of the navigable segment; The connectivity of this segment to other navigable segments. The method of claim 9 or claim 10, wherein the method is configured to determine that the travel time in the map will be slower than a predetermined threshold, and the navigable segments in the area are associated with the electronic map The other areas are separated. A method of t-month item 9 or claim 1 , configured to separate the navigable segment of the island/the other region of the electronic map by means of determining the property of the navigator Line to perform this separation. a method for generating map data, the map material comprising: configured to increase: a search acceleration that can be used to plan a route on an electronic map; and the method includes using at least one processing device to process a plurality of inclusions 150831.doc An electronic map of 201211509 navigable segments, each of which represents a segment of a navigable route in an area covered by the map, the method comprising: a) dividing the map into at least one coarser rank And a plurality of hierarchical regions adjacent to the finer level, such that each of the navigable segments is classified into at least one of the coarser level and the finer level, and wherein the coarser Level of responsibilities - the zone contains a plurality of zones of the finer level; b) for a given destination area, by evaluating whether a zone close to the coarser zone containing the target zone should be added to a visibility zone and Adding the zones when the evaluation is affirmative and determining the range of the visibility zone containing at least the coarser grade zone containing the destination zone; c) At least some navigable segments, calculating information about at least one least cost route to a region of interest; d) wherein processing the pair of navigation segments includes performing a reverse search from the destination region in turn toward one of the navigable segments, And substantially only includes the navigable segment in the visibility region of the destination area; and e) generating the map material. 15. A method of generating map data, the map material comprising search acceleration data configured to increase a speed at which a route can be planned on an electronic map, the method comprising using at least one processing device to process a plurality of navigable An electronic map of segments, each of the plurality of navigable segments respectively representing a segment of a navigable route in an area covered by the map, the method comprising: 150831.doc 201211509 a) dividing the δ meta-map into at least one coarser a plurality of hierarchical regions of a rank and an adjacent finer level such that each navigable segment is classified into at least one of the coarser rank and each of the finer ranks, and wherein the comparison Any of the coarser levels contains a plurality of zones of the finer level; _b) for a given destination area, by evaluating whether a zone close to the coarser zone containing the destination zone should be added to a visibility a region and adding the zones when the evaluation is positive to determine a range of the visibility zone containing at least the coarser zone containing the destination zone C) calculating, for at least some navigable segments, information about at least one least cost route to the region of interest; d) configuring the search acceleration profile to include some and usually each navigable segment in the visibility region Information on at least the least cost route to the destination area; and e) generating the map material. 16. 17. 18. The method of claim 14 or claim 15, wherein the assessment in step 是否 is based on whether the zone is close to the coarser graded zone containing the target zone based on the following A predetermined criterion for either or combination: graph theoretical distance, geographic distance, travel time, fuel consumption, and/or (10) emissions. The method of claim 15 or claim 16, wherein the step b evaluates an area adjacent to the coarser level region containing the region of interest. The method of claim 15 or claim 16 wherein the zone added to the visibility area comprises at least one of: the coarser level _ 150831.doc 201211509 or a plurality of zones and one of the coarser ranks Or part of multiple zones. The method of claim 15 or claim 16, wherein the search acceleration data includes at least an additional route other than the least cost route, wherein the additional route may reflect any one or more of the following: Different minimum cost routes at different times between a given departure point and a destination point; different minimum cost routes between the given departure point and the destination point for different traffic situations; according to different cost functions at a given starting point and destination Different minimum cost routes between locations; different minimum cost routes between a given departure point and destination point for any dynamic change in a given road network; according to the same cost function at a given departure point and destination point Alternative routes between; and different destination points in a similar direction to each other. 2. A method of generating map data, the map material comprising search acceleration data configured to increase a speed at which a route can be planned on an electronic map, the method comprising using at least one processing device to process a plurality of An electronic map of the navigation segment, the plurality of navigable segments each representing a segment of a navigable route in an area covered by the map, the method comprising: a) dividing the map into one or more levels a plurality of hierarchical areas; b) processing a specific level belonging to one of the levels in the order of the hierarchical level. S150831.doc 0 201211509 At least some of the areas in the area, from the finest level to the most coarse level And determining, for at least some of the zones, which navigable segments enter and/or leave the zone; c) processing at least some of the navigable segments of the map to determine from the other Navigating at least one minimum cost route from the segment to the destination area; d) wherein the processing of the pair of navigable segments comprises performing the reverse from the destination region One of the navigation segments is reverse searched; e) in the resulting search map, for at least one region at the next finer level, identifying one of the regions of the next finer level, such that from the given region Each minimum cost path passes through at least one of the zones of the set, resulting in a correlation matrix; f) identifying, in the resulting search map, which navigable segments are not included in a different zone than from itself From any route to another destination, such that it can be considered a "non-transport segment" and removes non-transport segments for subsequent steps to reduce the navigable segments considered in these subsequent steps The number; g) wherein the generating the search acceleration data comprises using the correlation matrix to assign the search acceleration data to the 'non-transport segments that have been removed in all previous steps; and h) generating the map material. 21_At least one computing device configured to perform the method of any one of claims 1-6. 22. At least one computing device configured to perform the method of claim 17 s. 23 24 25 26 27 28 29 30. 31. 32. At least one computing device' is configured to perform the method of claim 8. At least one computing device configured to perform the method of any one of claims 9 to 3. At least one computing device&apos; configured to perform at least one computing device as claimed in item 0, which is configured to perform the method of any of the claims. At least one computing device configured to perform, as in claim 2, a method. A computer readable medium containing instructions that, when read onto a machine, cause the machine to perform any of the claims 1 to 6 or as a computing device as claimed in claim 21 To execute. A computer readable medium containing instructions that, when read onto = causes the machine to perform the method of claim 7 or as the computing device of claim 22. Two computer readable media containing instructions that, when read onto = cause the other machine H to perform the method of claim 8 or the computing device of claim 23. Z contains a computer readable medium of instructions which, when read onto a -2, cause the machine to perform as a computing device as claimed in claim 24, as claimed in claim 9 (d). - a computer readable medium containing instructions which, when read onto a machine of a 150831.doc 201211509, cause the machine to perform a method such as the method of claim 14 or the computing device of claim 25 To execute. 33. 34. 35. 36. 37. 38. 39. A computer with instructions that can be used to confuse the media, such as when the instructions are read onto a machine, so that the machine is arrogant The method of any one of clauses 15 to 19 or as the computing device of claim 26. - A computer readable medium containing instructions that, when read onto a device, cause the device to perform a method as claimed or as a leaf device as claimed in claim 27. a navigation device configured to use its processor to generate a route on an electronic map, wherein the Henlu process is configured to: perform a route search on the electronic map; during the search In a cost calculation at the point of the navigable segment in the electronic map of the table, Μ Α β 仃 仃 仃 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可 可One of the parts of the route is evaluated; and if there is such a navigable segment on the right, then the J value is a navigable segment. A method of providing route planning, provided. The navigation device of claim 35 is a computer readable medium containing instructions. The seeker makes the machine act as a requester 36 when it is taken by the machine. The benefit of item 5 or the provision of any of the methods of requesting to 20, the search acceleration data, which is produced by a computer readable medium, such as a request item. , 3, like the search acceleration of claim 38, 150831.doc • 11 - 201211509 40. A navigation device that is configured to analyze map data using one of its processors to generate a destination on an electronic map a route, wherein the processor is configured to: perform a route search on the electronic map using information maintained in the map material; at a node processed during the search that represents a navigable segment in the electronic map - in the cost calculation, performing an evaluation of whether the navigable segment connected to the nodes is marked as one of the parts of the search acceleration f_the minimum cost route; wherein the map material includes whether there is a self-node to the purpose Additional search for the __ indicator of the acceleration data, the additional search acceleration data providing additional information about the least cost route; and if the additional search acceleration data is available, only the search is marked as _minimum in the additional search acceleration data The segments of the cost route are part of them. 150831.doc