Systems and methods for determining connectivity scores for area metric tiles in geospatial datasets

Abstract

A system and method are provided for calculating the connectivity score of each regional metric tile in a geospatial dataset. The method involves identifying vehicle locations, identifying one or more target regional metric tiles, receiving or accessing information related to parameters affecting connectivity between vehicles and a cloud-based backend, and determining the connectivity score of each target regional metric tile based on a weighted average of these parameters. Any target regional metric tile with a connectivity score less than a minimum connectivity threshold is characterized as a dead zone, which is added to a Dynamic Dead Zone Tile List (DDTL), and actions are performed based on the DDTL.

Description

[0001] introduce

[0002] This disclosure relates to systems and methods for determining connectivity scores of regional metric tiles in a geospatial dataset.

[0003] Self-driving or driver-assisted motor vehicles utilize digital maps of the surrounding terrain to assist driving. For example, these digital maps may include geohash information associated with rectangular geohash tiles of various sizes.

[0004] A geographic queue is a prioritized list of geohash tiles (or other regional metric tiles) that a vehicle is configured to download based on various heuristics executed on the vehicle. In systems based on static geographic queues, performance or map availability is highly variable due to network congestion and connectivity issues. When a vehicle enters an area lacking network coverage for an extended period, a static geographic queue may fail to download all the tiles required for driving. Aggressive approaches that attempt to download all possible tiles increase data costs as the system scales. Summary of the Invention

[0005] According to one embodiment, a method is provided for determining a corresponding connectivity score for each of a plurality of regional metric tiles in a geospatial dataset. The method includes: (i) identifying the vehicle location of a motor vehicle; (ii) identifying one or more target regional metric tiles, the target regional metric tiles including one or more of the following: a current regional metric tile where the vehicle location is situated, one or more surrounding regional metric tiles directly surrounding the current regional metric tile, and one or more upcoming regional metric tiles that the motor vehicle is expected to pass through; (iii) receiving or accessing information for each of the target regional metric tiles related to a plurality of parameters affecting connectivity between the motor vehicle and a cloud-based backend; and (iv) weighting the scores based on the plurality of parameters. (v) Determine the corresponding connectivity score for each target area measurement tile in the target area measurement tiles by the mean; (vi) Determine which target area measurement tiles in the target area measurement tiles have a corresponding connectivity score less than a minimum connectivity threshold, thereby defining each such target area measurement tile as a dead zone; (vi) Add each dead zone to a dynamic dead zone tile list (DDTL); and (vii) Perform an action based on the DDTL, wherein the action includes one or more of the following: transmitting the DDTL to the motor vehicle, prefetching map data for the target area measurement tiles, and causing a change in the operating state of the motor vehicle.

[0006] Each region metric tile can be an L5 geoscrambled tile.

[0007] The plurality of regional metric tiles may include one or more large geohash tiles and one or more small geohash tiles, wherein each large geohash tile has a first geohash with a first number of alphanumeric characters, and each small geohash tile has a second geohash with a second number of alphanumeric characters greater than the first number.

[0008] For each target area measurement tile, the plurality of parameters may include two or more of the following: cellular network signal strength, vehicle-reported signal quality / strength, weather-related signal interference, and signal obstruction impact. Each of these parameters may have a corresponding weight, and the weighted average may be the sum of each parameter multiplied by its corresponding weight. For each target area measurement tile, the connectivity score may be represented by C, which may be represented by a first set {P1, P2, P3, P4, ...}, and the weights may be represented by a second set {w1, w2, w3, w4, ...}, where C = (w1 × P1) + (w2 × P2) + (w3 × P3) + (w4 × P4) + ...).

[0009] Each dead zone can be stored in DDTL along with its associated parameters.

[0010] The method may also include detecting a handshake with the motor vehicle, wherein the handshake occurs at the start of the key cycle of the motor vehicle.

[0011] Changes in operational status may include at least one of the following: taking actions aimed at increasing the corresponding connectivity score of one or more target area metric tiles, changing one or more conditions related to the assisted driving mode, and modifying the scheduling of one or both of receiving downloads from the background and sending uploads to the background.

[0012] Actions may include making route changes aimed at increasing the corresponding connectivity scores of one or more target area metric tiles.

[0013] Changing one or more conditions may include one or more of the following: enabling driver assistance mode, disabling driver assistance mode, and activating connectivity alerts.

[0014] Downloads may include one or more of the following: firmware updates, configuration updates, and information packages.

[0015] DDTL can be hosted in a cloud-based backend.

[0016] Steps (i) to (vii) can be implemented by a controller configured to receive input signals and send output signals, wherein each of the input signals and output signals is one or both of a command signal and a data signal.

[0017] According to another embodiment, a method is provided for determining a corresponding connectivity score for each of a plurality of geohash tiles in a geospatial dataset. The method includes: (i) identifying the vehicle location of a motor vehicle using a controller; (ii) identifying one or more target geohash tiles using the controller, wherein the one or more target geohash tiles include one or more of the following: the current geohash tile where the vehicle location is located, one or more surrounding geohash tiles directly surrounding the current geohash tile, and one or more upcoming geohash tiles that the motor vehicle is expected to pass through; (iii) receiving or accessing information for each of the target geohash tiles using the controller, wherein the information is related to a plurality of parameters affecting connectivity between the motor vehicle and a cloud-based backend; and (iv) determining the target geohash tile using the controller. (v) determining, by using the controller, which target geohash tiles have a corresponding connectivity score less than a minimum connectivity threshold, thereby defining each such target geohash tile as a dead zone; (vi) adding each dead zone to a Dynamic Dead Zone Tile List (DDTL) by using the controller; and (vii) performing an action based on the DDTL by using the controller, wherein the action includes one or more of the following: transmitting the DDTL to the vehicle, prefetching map data for the target geohash tiles, and causing a change in the operating state of the vehicle.

[0018] According to another embodiment, a system is provided for determining a corresponding connectivity score for each of a plurality of regional metric tiles in a geospatial dataset. The system includes: (i) a positioning module configured to identify the vehicle location of a motor vehicle; (ii) a targeting module configured to identify one or more target regional metric tiles, the target regional metric tiles including one or more of the following: a current regional metric tile where the vehicle location is situated, one or more surrounding regional metric tiles directly surrounding the current regional metric tile, and one or more upcoming regional metric tiles that the motor vehicle is expected to pass through; (iii) a receiving module configured to receive or access information for each of the target regional metric tiles relating to a plurality of parameters affecting connectivity between the motor vehicle and a cloud-based backend; (iv) a scoring module configured to determine a corresponding connectivity score for each of the target regional metric tiles based on a weighted average of the plurality of parameters; and (v) a comparison module configured to determine which of the target regional metric tiles have a corresponding connectivity score less than a minimum connectivity threshold. Each such target area measurement tile is thus defined as a dead zone; (vi) an adding module configured to add each dead zone to a dynamic dead zone tile list (DDTL); (vii) an execution module configured to perform an action based on the DDTL, wherein the action includes one or more of the following: transmitting the DDTL to the vehicle, prefetching map data for the target area measurement tiles, and causing a change in the operating state of the vehicle; and (viii) a controller operatively connected to the positioning module, the target module, the receiving module, the scoring module, the comparison module, the adding module, and the execution module, wherein the controller is configured to: (a) receive input signals from one or more of the positioning module, the target module, the receiving module, the scoring module, the comparison module, the adding module, and the execution module, and (b) send output signals to one or more of the positioning module, the target module, the receiving module, the scoring module, the comparison module, the adding module, and the execution module.

[0019] The system may also include a detection module configured to detect handshakes with a motor vehicle, wherein the controller is also operatively connected to the detection module and configured to receive input signals from the detection module and send output signals to the detection module. Each of the input and output signals may be one or both of a command signal and a data signal.

[0020] DDTL can be hosted in a cloud-based backend.

[0021] For each target area metric tile, the plurality of parameters may include two or more of the following: cellular network signal strength, vehicle-reported signal quality / strength, weather-related signal interference, and signal obstruction effects, each parameter may have a corresponding weight, and the weighted average may be the sum of each parameter multiplied by its corresponding weight.

[0022] This disclosure provides the following examples:

[0023] Example 1. A method for determining the corresponding connectivity score for each of multiple regional metric tiles in a geospatial dataset, comprising:

[0024] (i) Identify the vehicle location of the motor vehicle;

[0025] (ii) Identify one or more target area measurement tiles, the target area measurement tiles including one or more of the following: the current area measurement tile where the vehicle is located, one or more surrounding area measurement tiles directly around the current area measurement tile, and one or more upcoming area measurement tiles through which the vehicle is expected to travel.

[0026] (iii) Receive or access information about each of the target area metric tiles relating to multiple parameters affecting the connectivity between the vehicle and the cloud-based backend;

[0027] (iv) Determine the corresponding connectivity score for each of the target region metric tiles based on the weighted average of the plurality of parameters;

[0028] (v) Determine which of the target region metric tiles have a corresponding connectivity score less than the minimum connectivity threshold, thereby defining each such target region metric tile as a dead zone;

[0029] (vi) Add each dead zone to the Dynamic Dead Zone Tile List (DDTL); and

[0030] (vii) Perform an action based on the DDTL, wherein the action includes one or more of the following: transmitting the DDTL to the motor vehicle, prefetching map data for the target area measuring tiles, and causing a change in the operating state of the motor vehicle.

[0031] Example 2. The method described in Example 1, wherein each of the said regional metric tiles is an L5 geohash tile.

[0032] Example 3. According to the method of Example 1, the plurality of regional metric tiles may include one or more large geohash tiles and one or more small geohash tiles, wherein each large geohash tile has a first geohash having a first number of alphanumeric characters, and each small geohash tile has a second geohash having a second number of alphanumeric characters greater than the first number.

[0033] Example 4. According to the method of Example 1, wherein, for each target area metric tile, the plurality of parameters includes two or more of the following:

[0034] Cellular network signal strength;

[0035] The vehicle reported the signal quality / strength;

[0036] Weather-related signal interference; and

[0037] Signal obstruction.

[0038] Example 5. According to the method of Example 4, each of the parameters has a corresponding weight, and the weighted average is the sum of the parameters multiplied by their respective weights.

[0039] Example 6. According to the method described in Example 5, wherein for each target region metric tile, the connectivity score is represented by C, the parameters are represented by a first set {P1,P2,P3,P4}, and the weights are represented by a second set {w1,w2,w3,w4}, where C = (w1×P1) + (w2×P2) + (w3×P3) + (w4×P4).

[0040] Example 7. The method described in Example 1, wherein each dead zone, together with its associated parameters, is stored in the DDTL.

[0041] Example 8. The method described in Example 1 further includes:

[0042] Detect the handshake with the motor vehicle;

[0043] The handshake occurs at the start of the key cycle of the motor vehicle.

[0044] Example 9. The method according to Example 1, wherein the change in the operating state includes at least one of the following:

[0045] Take one or more actions aimed at increasing the corresponding connectivity score of the metric tiles in the target area;

[0046] Change one or more conditions associated with the driver assistance mode; and

[0047] Modify the scheduling for receiving downloads from the backend and sending uploads to the backend, or both.

[0048] Example 10. The method according to Example 9, wherein the action includes making a route change aimed at increasing one or more of the corresponding connectivity scores of the target area metric tiles.

[0049] Example 11. The method according to Example 9, wherein changing one or more conditions includes one or more of the following: enabling the driver assistance mode, disabling the driver assistance mode, and activating the connectivity alarm.

[0050] Example 12. The method according to Example 9, wherein the download includes one or more of firmware updates, configuration updates, and information packets.

[0051] Example 13. The method according to Example 1, wherein the DDTL is hosted in the cloud-based backend.

[0052] Example 14. The method according to Example 1, wherein steps (i) to (vii) are implemented by a controller configured to receive input signals and send output signals, wherein each of the input signals and the output signals is one or both of a command signal and a data signal.

[0053] Example 15. A method for determining the corresponding connectivity score for each of multiple geospatial tiles in a geospatial dataset, comprising:

[0054] The location of motor vehicles is identified by using a controller;

[0055] The controller is used to identify one or more target geohash tiles, wherein the one or more target geohash tiles include one or more of the following: the current geohash tile where the vehicle is located, one or more surrounding geohash tiles directly around the current geohash tile, and one or more upcoming geohash tiles that the vehicle is expected to pass through.

[0056] The controller receives or accesses information for each of the target geospatial tiles, wherein the information is related to multiple parameters affecting the connectivity between the vehicle and the cloud-based backend.

[0057] The controller is used to determine the corresponding connectivity score for each of the target geospatial tiles, wherein the connectivity score is based on a weighted average of the plurality of parameters;

[0058] By using the controller to determine which target geohash tiles have a corresponding connectivity score less than the minimum connectivity threshold, each such target geohash tile is defined as a dead zone.

[0059] Each dead zone is added to the Dynamic Dead Zone Tile List (DDTL) using the controller; and

[0060] The controller performs actions based on the DDTL, wherein the actions include one or more of the following: transmitting the DDTL to the vehicle, prefetching map data for the target geospatial tiles, and causing changes in the operating state of the vehicle.

[0061] Example 16. A system for determining a corresponding connectivity score for each of multiple regional metric tiles in a geospatial dataset, comprising:

[0062] The positioning module is configured to identify the vehicle location of a motor vehicle;

[0063] The target module is configured to identify one or more target area measurement tiles, the target area measurement tiles including one or more of the following: the current area measurement tile where the vehicle is located, one or more surrounding area measurement tiles directly around the current area measurement tile, and one or more upcoming area measurement tiles that the vehicle is expected to pass through.

[0064] The receiving module is configured to receive or access information for each of the target area measurement tiles related to multiple parameters affecting the connectivity between the vehicle and the cloud-based backend;

[0065] A scoring module is configured to determine a corresponding connectivity score for each of the target region metric tiles based on a weighted average of the plurality of parameters;

[0066] The comparison module is configured to determine which target region metric tiles among the target region metric tiles have a corresponding connectivity score less than a minimum connectivity threshold, thereby defining each such target region metric tile as a dead zone;

[0067] Add a module and configure it to add each dead zone to the Dynamic Dead Zone Tile List (DDTL);

[0068] An execution module is configured to perform actions based on the DDTL, wherein the actions include one or more of the following: transmitting the DDTL to the vehicle, prefetching map data for measuring tiles of the target area, and causing a change in the operating state of the vehicle; and

[0069] A controller, operatively connected to the positioning module, the target module, the receiving module, the scoring module, the comparison module, the adding module, and the execution module, wherein the controller is configured for one or both of the following:

[0070] Receive input signals from one or more of the positioning module, the target module, the receiving module, the scoring module, the comparison module, the adding module, and the execution module; and

[0071] The system sends an output signal to one or more of the positioning module, the target module, the receiving module, the scoring module, the comparison module, the adding module, and the execution module.

[0072] Example 17. The system according to Example 16 further includes:

[0073] A detection module is configured to detect handshakes with the motor vehicle;

[0074] The controller is also operatively connected to the detection module and is further configured for one or both of the following:

[0075] Receive input signals from the detection module; and

[0076] The output signal is sent to the detection module.

[0077] Example 18. The system according to Example 17, wherein each of the input signal and the output signal is one or both of a command signal and a data signal.

[0078] Example 19. The system according to Example 16, wherein the DDTL is hosted in the cloud-based backend.

[0079] Example 20. The system according to Example 16, wherein:

[0080] For each target area metric tile, the multiple parameters include two or more of the following: cellular network signal strength, vehicle-reported signal quality / strength, weather-related signal interference, and signal obstruction effects;

[0081] Each of the parameters has a corresponding weight; and

[0082] The weighted average is the sum of the parameters multiplied by their respective weights.

[0083] The foregoing features and advantages of this teaching, as well as other features and advantages, will become apparent from the following detailed description of some of the best modes and other embodiments for carrying out this teaching as defined in the appended claims when considered in conjunction with the accompanying drawings. Attached Figure Description

[0084] Figure 1 This is a schematic diagram of a vehicle communicating with a cloud-based backend.

[0085] Figure 2 This is a map showing the selected L4 geographic scatter tiles.

[0086] Figure 3 It shows the relationship with Figure 2 The same map, but subdivided into thirty-two L5 geographic scatter tiles.

[0087] Figure 4 This is a schematic diagram of an L5 geospatial tile selected from a geospatial dataset, overlaid with a fault zone.

[0088] Figure 5 yes Figure 4 The diagram on the right shows the expected vehicle path.

[0089] Figure 6 It is a graphic comparing the large L4 geospatial tile with the small L5 geospatial tile.

[0090] Figure 7 It is a set of equations that describe the first set of parameters, the second set of weights, and the equations used to calculate the connectivity score.

[0091] Figure 8 This is a flowchart of a method for determining the connectivity score of regional metric tiles in a geospatial dataset.

[0092] Figure 9 This is a block diagram of a system for determining the connectivity scores of regional metric tiles in a geospatial dataset. Detailed Implementation

[0093] Referring now to the accompanying drawings, in which similar reference numerals in several views indicate similar parts, this document shows and describes a system 20 and a method 100 for determining the connectivity score C of regional metric tiles 14 in a geospatial dataset 19.

[0094] Figure 1 A schematic diagram is shown of a motor vehicle V1 communicating with cloud 10 (i.e., the Internet) via cellular phone signals, radio, or other electromagnetic frequencies. In some embodiments, motor vehicle V1 may be able to operate in an assisted driving mode (which may optionally include a fully automated driving mode). A cloud-based backend 11 exists or is hosted within cloud 10. A dynamic dead zone tile list, or “DDTL” (described in further detail below), also exists or is hosted within cloud 10, where backend 11 has access to the DDTL.

[0095] Figure 2 A road map is shown, defined by rectangles that enclose the selected L4 geospatial tile 13. L4 In comparison, Figure 3 It shows the relationship with Figure 2 A map of the same area, but this map is subdivided into 32 smaller L5 geospatial tiles. L5 L4 Geographic Scattered Tiles 13 L4 And L5 geographically scattered tiles 13 L5 These are all examples of geographically scattered tiles 13.

[0096] Figure 4 A schematic diagram of selected regional metric tiles 14 (e.g., geospatial tiles 13) is shown, but no road maps are shown. The set of regional metric tiles 14 represents a portion of a much larger geospatial dataset 19 (such as a global set of regional metric tiles 14 covering the planet Earth). Although Figure 2-4 For details, please refer to L4 and / or L5 geospatial tile 13. L4 13 L5 However, it should be noted that the scope of this disclosure is not limited to L4 and L5 geospatial tiles 13 L4 13 L5 The system is not limited to the system or hierarchy of the geospatial tile 13, but can be extended to any regional metric that divides the geospatial dataset 19 of the Earth's surface into smaller, organized subdivisions, such as hexagonal H3 tiles / coordinates, oceanic tiles / coordinates, smooth tiles, etc. As used herein, a "regional metric" tile 14 is a region, parcel, sector, or tile on the Earth's surface with defined boundaries that surround the defined region. Each such regional metric tile 14 may have its own unique identifier, location, hash, handle, etc., to identify the regional metric tile and distinguish it from all other regional metric tiles 14 of the same type. Therefore, while the system 20 and method 100 of this disclosure are described at some points herein based on the geospatial tile 13, this is merely for illustrative purposes, and the scope of the regional metric tile 14 is not limited to the geospatial tile 13.

[0097] Figure 4Overlaid on the selected geographic hash or regional metric tiles 13, 14 are several “fault zones” where the connectivity between the background 11 and one or more vehicles V1, V2 within those fault zones has been compromised in one or more ways. For example, a first fault zone 15 is shown in the upper left of the figure, defined by dotted lines and having diagonal crosshairs. This first fault zone 15 may be an area experiencing a network outage. A second fault zone 16 is shown directly to the right of the first fault zone 15 and overlaps with it. This second fault zone 16 is defined by a large, thick dashed line and may be an area experiencing poor network coverage. A third fault zone 17 is shown in the lower left of the figure and partially overlaps with the second fault zone 16. This third fault zone 17 is defined by small, light dashed lines and filled with dots; this may be an area experiencing High Speed ​​Vehicle Telemetry (HSVT) connectivity problems or faults, which overlaps with a portion of the second fault zone 16. (These HSVT issues or faults may involve any type of communication between vehicle V1 and a remote server (such as backend 11), where vehicle V1 reports various types of time-stamped telemetry data, such as its position, speed and heading, connectivity strength or signal quality measured by vehicle V1, etc.) Finally, a fourth area 18 (but not a “fault” area) is shown on the right side of the figure, where satisfactory connectivity is provided (i.e., there are no significant “faults”).

[0098] like Figure 4 As shown, the vehicle has a first vehicle position L V1 The first vehicle V1 is shown within the fourth region 18, where the current direction of travel vector points downwards to the left. The first vehicle V1 is located within the fourth region 18, which provides good network connectivity, in the direct geographic hash or area measurement tiles 13, 14, and those surrounding the first vehicle V1 and along its first intended path AP1. Conversely, the location of the second vehicle L is shown in the lower left of the figure. V2 The second vehicle V2, which proceeds along the second intended path AP2 (indicated by an upward arrow), will soon reach the third fault zone 17 where HSVT connectivity / telemetry problems or faults exist. If the second vehicle V2 continues along the indicated path AP2, it may also encounter additional connectivity problems as it travels through the first and / or second fault zones 15, 16.

[0099] In this example, if the first vehicle V1 and the second vehicle V2 are in an autonomous or assisted driving mode (or the driver wishes to enter one of these modes), it would be beneficial for the driver and the autonomous or assisted driving system to be aware that the first vehicle V1 or the second vehicle V2 is already in or about to enter a fault zone, because some types of network connectivity issues may affect the ability of the autonomous or assisted driving system to function properly.

[0100] Figure 5 It shows Figure 4 The schematic diagram on the right shows the expected path AP1 and destination D1 of the first vehicle V1. As mentioned above, the individual tiles can be various types and sizes of area measurement tiles 14, such as geohash tiles 13. Various types of target area measurement tiles 14t (e.g., target geohash tiles 13t) are shown in the figure. The first vehicle V1 and its location L are also shown. V1 The currently located tile can be referred to as the current region metric tile 14c (e.g., the current geohash tile 13c), and the tiles surrounding the current region metric or geohash tiles 14c, 13c can be referred to as the surrounding region metric or geohash tiles 14s, 13s. These surrounding tiles 13s, 14s can include tiles adjacent to or contacting the current tiles 13c, 14c, and may also optionally include tiles spaced apart from the current tiles 13c, 14c by one or more tiles. Along the expected path AP1 of vehicle V1, one or more upcoming region metric or geohash tiles 14u, 13u can be found. Figure 5 It is important to note that the surrounding tiles 13s and 14s have a lowercase "s" in each tile, while the upcoming tiles 13u and 14u have a lowercase "u" in each tile.

[0101] As from Figure 2-4 As you can see, each map or geographical region can be broken down into rectangular (or other shaped) tiles of various sizes. For example, Figure 2 and Figure 3 The map shown indicates that a single large geohash tile 13 can be subdivided into thirty-two smaller geohash tiles 14. Although not shown in the accompanying figures, L5 geohash tiles 14 can be subdivided into thirty-two L6 geohash tiles, and those can be further subdivided into even smaller L7 geohash tiles, and so on. Note that, as used herein, the terms “large,” “larger,” “small,” and “smaller” can be used to distinguish two different tiles according to their respective sizes; thus, a “large” tile will be larger than a “small” tile, and a “small” tile will be smaller than a “large” tile.

[0102] Each geohash tile 13 has an associated "geohash identifier," often simply referred to as a "geohash." For example, Figure 6 The diagram shown will be compared with the larger L4 geographic scatter tile 13 L4 The associated first geohash 13g1 and the smaller L5 geohash tile 13 L5 The associated second geohash 13g2 is compared. In this example, the larger L4 geohash tile 13... L4The first geohash 13g1 has "dpsc" and is four alphanumeric characters long, while the smaller L5 geohash tile 13... L5 The second geohash 13g2 has the digit "dpscz" and is five alphanumeric characters long. Furthermore, Table 1 below shows the breakdown of all thirty-two five-digit L5 geohash 13g2, which are part of the first geohash 13g1 "dpsc", arranged in four rows and eight columns.

[0103] Table 1 shows the L5 geohashes within the L4 geohash "dpsc".

[0104] Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 Line 4 dpscb dpscc dpscf dpscg dpscu dpscv dpscy dpscz Line 3 dpsc8 dpsc9 dpscd dpsce dpscs dpsct dpscw dpscx Line 2 dpsc2 dpsc3 dpsc6 dpsc7 dpsck dpscm dpscq dpscr Line 1 dpsc0 dpsc1 dpsc4 dpsc5 dpsch dpscj dpscn dpscp

[0105] Using the aforementioned information about regional metric tiles 14 and connectivity issues, a method 100 can be generated to determine the connectivity scores C of various regional metric tiles 14 within the geospatial dataset 19. Figure 7 A set of equations that can be used with method 100 is shown, and Figure 8 A flowchart of method 100 is shown. Method 100 can be executed by background 11, by an individual motor vehicle V1, by a group of motor vehicles V1, V2, or by some combination of the foregoing.

[0106] Method 100 begins at box 110, and at box 120, determines whether a handshake HS has been detected from vehicle V1 (e.g., by background 11). The handshake HS may occur at the start of each key cycle KC of vehicle V1. If no handshake HS has been detected with vehicle V1, an optional first delay may be performed at box 130; this optional delay may be included to reduce the frequency at which box 120 is performed. On the other hand, if a handshake HS has been detected, the process flow proceeds to box 140.

[0107] At box 140, the "previous DDTL" can be initialized (i.e., set to an empty set), and at box 150, it is determined whether vehicle V1 is still connected (e.g., connected to backend 11). The presence of this connection indicates that vehicle V1 is still in its current key cycle KC. If vehicle V1 is still not connected, method 100 ends at box 160, but if vehicle V1 is still connected, the process moves to box 170.

[0108] At box 170, identify the vehicle position L of motor vehicle V1. V1 Furthermore, at frame 180, one or more target area measurement tiles 14t are identified. The target area measurement tile 14t may include vehicle V1 and vehicle position L. V1The current area measurement tile 14c in which the vehicle V1 is located, one or more surrounding area measurement tiles 14s directly around the current area measurement tile 14c, and / or one or more upcoming area measurement tiles 14u that the vehicle V1 is expected or predicted to pass through.

[0109] At box 190, information 12 relating to various parameters P affecting connectivity is received or accessed. These parameters P may include cellular network signal strength P1 (as reported by one or more operators / providers in a region or area), vehicle-reported signal quality and / or signal strength P2 (as measured at and reported by one or more vehicles V1, V2, etc.), weather-related signal interference P3, and signal obstruction effects P4, etc. The vehicle-reported signal quality / strength P2 may reflect the actual cellular network signal strength and / or (one or more) other network parameters measured by each vehicle V1, V2, etc. at their respective locations and times. These other network parameters may include download speed, upload speed, latency, bandwidth, quality of service, etc. Since the actual cellular network signal strength and / or other network parameters may be reported multiple times by multiple vehicles at multiple locations, these data points may form or represent a multidimensional matrix of parameter values. To distill these various data points into a single usable value, the vehicle-reported signal quality / strength P2 may be the average, median, mode, or some other measure or combination of these various data points. Weather-related signal interference P3 can reflect the level and / or type of ground and space weather phenomena (such as thunderstorms, sunspot activity, etc.) that interfere with network connectivity. Signal obstruction impact P4 can reflect the proximity, height, and number or density of obstacles or driving-impeding conditions (such as buildings, mountains, driving in tunnels, etc.). The specific values ​​of these parameters P can vary from one small area measured by tile 14 to another.

[0110] At box 200, a corresponding current connectivity score C is determined for each target region metric tile 14t. The connectivity score C is based on a weighted average of the various parameters P described above, where each parameter P has a corresponding weight w. The weighted average can be calculated as the sum of the parameters P multiplied by their corresponding weights w. For example, for each target region metric tile 14t, the connectivity score can be represented by C, the parameters P can be represented by a first set {P1, P2, P3, P4, ...}, and the weights w can be represented by a second set {w1, w2, w3, w4, ...}, where C = (w1 × P1) + (w2 × P2) + (w3 × P3) + (w4 × P4) + ...). However, while this example utilizes four parameters P and weights w, it can be noted that only two parameters P and weights w are needed to calculate the connectivity score C, and any number of parameters P and corresponding weights w greater than two can be used.

[0111] At box 210, determine which target regions have a connectivity score C of tile 14t that is less than the minimum connectivity threshold C. min Thus, each such target area metric tile 14t is defined as a dead zone DZ, in which network connectivity problems may occur.

[0112] At box 220, any dead zones (DZs) found are added to the dynamic dead zone tile list DDTL (e.g., "current DDTL"), which is a collection of all current dead zone DZs found within the target area measurement tile 14t. Each dead zone DZ can be stored in the DDTL along with a specific value of its associated parameter P.

[0113] At box 230, it is checked whether the current DDTL is different from the previous DDTL. If not, the process proceeds to box 240, where the previous DDTL is set to be equal to the current DDTL, and an optional second delay can be performed at box 250. However, if the current DDTL is different from the previous DDTL, the process moves to box 260, where an action based on the current DDTL is performed.

[0114] The actions taken in box 260 may include one or more of the following: transmitting DDTL to vehicle V1, prefetching map data for the target area measurement tile 14t, and causing a change in the operating state of vehicle V1.

[0115] Changes in operational status may include at least one of the following: taking actions aimed at increasing the corresponding connectivity score C of the target area metric tile 14t; changing one or more conditions related to the assisted driving mode; and modifying the scheduling for receiving a download from the background 11 and sending an upload to the background 11, or both. Downloads may include one or more of firmware updates, configuration updates, and information packets.

[0116] Actions taken may include route changes (i.e., a change of direction to follow a different path) aimed at increasing one or more of the corresponding connectivity scores C of the target area metric tile 14t.

[0117] Changing one or more conditions may include one or more of the following: enabling driver assistance mode, disabling driver assistance mode, and activating connectivity alerts (e.g., lights on the steering wheel or dashboard, audible alarms, etc.).

[0118] Method 100 can be executed again at the beginning of the next key cycle KC of the motor vehicle V1 or at any other desired time or frequency. The dead zone DZ information stored in the DDTL can be used for various purposes, such as for assisted or fully autonomous driving, as well as for navigation, route correction, managing the uploading and downloading of firmware patches / updates, configuring patches / updates, information packets, map data, etc.

[0119] It should also be noted that even when no handshake HS with vehicle V1 is detected, the cloud-based backend 11 can still perform data collection, analysis, and aggregation processes to construct a very large DDTL covering a wide area and / or multiple areas of dead zone DZ. The backend 11 can achieve this by receiving or accessing information 12 (in box 190) related to various parameters P of the area metric tiles 14 for the wide area / multiple areas, determining the connectivity scores C of these area metric tiles 14 (in box 200), and determining which tiles 14 have connectivity scores C less than a minimum connectivity threshold C. min (in box 210) and add these tiles 14 that are smaller than the minimum connectivity threshold as dead zones DZ to very large DDTLs (in box 220).

[0120] Figure 9 A block diagram of a system 20 for determining the connectivity score C of regional metric tiles 14 in a geospatial dataset 19 is shown. System 20 includes a positioning module 28, a target module 30, a receiving module 32, a scoring module 34, a comparison module 36, an adding module 38, an execution module 44, and a controller 50. System 20 may also optionally include various other modules, as described below.

[0121] The positioning module 28 is configured to identify the vehicle position L of motor vehicle V1. V1 .

[0122] Target module 30 is configured to identify one or more target area measurement tiles 14t, the target area measurement tiles 14t including vehicle location L V1 The current area measurement tile 14c in which it is located, one or more surrounding area measurement tiles 14s directly around the current area measurement tile 14c, and / or one or more upcoming area measurement tiles 14u that the motor vehicle V1 is expected to pass through.

[0123] The receiving module 32 is configured to receive or access information 12 of each target area measurement tile 14t related to various parameters P affecting the connectivity between the motor vehicle V1 and the backend 11.

[0124] The scoring module 34 is configured to determine the connectivity score C of each target area metric tile 14 based on a weighted average of parameter P.

[0125] Comparison module 36 is configured to determine which target regions have a connectivity score C of 14t that is less than the minimum connectivity threshold C. min Thus, each such target area metric tile 14t is defined as the dead zone DZ.

[0126] Add module 38 is configured to add any dead zone DZ to the dynamic dead zone tile list DDTL.

[0127] The execution module 44 is configured to perform actions based on DDTL. The actions may include one or more of the following: transmitting DDTL to the vehicle V1, prefetching map data for the target area measurement tile 14t, and causing a change in the operating state of the vehicle V1.

[0128] Controller 50 is operatively connected to positioning module 28, target module 30, receiving module 32, scoring module 34, comparison module 36, adding module 28, and execution module 44. Controller 50 is configured to receive input signals 58 from one or more of positioning module 28, target module 30, receiving module 32, scoring module 34, comparison module 36, adding module 38, and execution module 44, or to send output signals 60 to one or more of positioning module 28, target module 30, receiving module 32, scoring module 34, comparison module 36, adding module 38, and execution module 44, or to receive and send both. Controller 50 may include a processor 52 operatively connected to a memory 54, in which instructions 56 are stored. For example, instructions 56 may include or be based on the steps of method 100 as described above.

[0129] Optionally, system 20 may also include a detection module 22 configured to detect a handshake HS with motor vehicle V1. In this arrangement, controller 50 is also operatively connected to detection module 22, and controller 50 is further configured to receive an input signal 58 from detection module 22, or to send an output signal 60 to detection module 22, or to receive and send both.

[0130] Each of the input and output signals 58 and 60 can be one or both of the command signal 62 and the data signal 64. Note that in Figure 8The diagram illustrates the connections between adjacent modules 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, and 44, and between the controller 50 and each of these modules. However, it should be noted that some of these connections may be optional. For example, when the receiving module 32 receives or accesses information 12 related to various parameters P, it can directly pass this information 12 to the scoring module 34, or it can route the information 12 to the controller 50, which then routes the information 12 to the scoring module 34.

[0131] The various configurations and embodiments of system 20 and method 100 presented herein can be implemented in a wide range of different applications and use cases, including use with electric or hybrid motor vehicles. For example, system 20 and method 100 can be implemented on-board in such a vehicle, or they can be implemented off-board, or some parts can be implemented on-board while others can be implemented off-board.

[0132] As those skilled in the art will understand, the system 20 and method 100 of this disclosure can be presented or arranged in various different configurations and embodiments.

[0133] According to one embodiment, a method 100 is provided for determining a corresponding connectivity score C for each of a plurality of regional metric tiles 14 in a geospatial dataset 19. Method 100 includes: (i) identifying the vehicle location L of motor vehicle V1 at box 170. V1 (ii) At box 180, identify one or more target area measurement tiles 14t, the target area measurement tiles 14t including one or more of the following: vehicle location L V1 (iii) At box 190, receiving or accessing information 12 related to each target area metric tile 14t in relation to multiple parameters P affecting connectivity between vehicle V1 and cloud-based backend 11; (iv) At box 200, determining a corresponding connectivity score C for each target area metric tile 14t based on a weighted average of the multiple parameters P; and (v) At box 210, determining which target area metric tiles 14t have a corresponding connectivity score C less than a minimum connectivity threshold C. minThus, each such target area metric tile 14t is defined as a dead zone DZ; (vi) at box 220, each dead zone DZ is added to the dynamic dead zone tile list DDTL; and (vii) at box 260, an action is performed based on the DDTL, wherein the action includes one or more of the following: transmitting the DDTL to the vehicle V1, prefetching map data for the target area metric tile 14t, and causing a change in the operating state of the vehicle V1.

[0134] Each region metric tile 14 can be an L5 geohash tile 13. L5 .

[0135] Multiple area measurement tiles 14 may include one or more large geographic hash tiles 13 L4 and one or more small geographically scattered tiles 13 L5 Each large geographically scattered tile has 13 tiles. L4 It has a first geographic hash 13g1, the first geographic hash 13g1 has a first number Q1 alphanumeric characters, and each small geographic hash tile has 13 L5 It has a second geographic hash 13g2, which has a second number Q2 alphanumeric characters greater than the first number Q1.

[0136] For each target area measurement tile 14t, the plurality of parameters P may include two or more of the following: cellular network signal strength P1, vehicle-reported signal quality / strength P2, weather-related signal interference P3, and signal obstacle impact P4. Each of the parameters P may have a corresponding weight w, and the weighted average may be the sum of the parameters P multiplied by their respective weights w. For each target area measurement tile 14t, the connectivity score may be represented by C, the parameters P may be represented by a first set {P1, P2, P3, P4, ...}, and the weights w may be represented by a second set {w1, w2, w3, w4, ...}, where C = (w1 × P1) + (w2 × P2) + (w3 × P3) + (w4 × P4) + ...).

[0137] Each dead zone (DZ) can be stored in the DDTL along with its associated parameter (P).

[0138] Method 100 may further include: (v) at block 120, detecting a handshake HS with the motor vehicle V1, wherein the handshake HS occurs at the beginning of each key cycle KC of the motor vehicle V1.

[0139] Changes in the operational state may include at least one of the following: taking actions aimed at increasing one or more of the corresponding connectivity scores C of the target area metric tile 14t, changing one or more conditions related to the assisted driving mode, and modifying the scheduling for receiving one or both of downloads from the background 11 and sending uploads to the background 11.

[0140] Taking action may include making route changes aimed at increasing one or more of the corresponding connectivity scores C of the target area metric tile 14t.

[0141] Changing one or more conditions may include one or more of the following: enabling driver assistance mode, disabling driver assistance mode, and activating connectivity alerts.

[0142] Downloads may include one or more of the following: firmware updates, configuration updates, and information packages.

[0143] DDTL can be hosted in a cloud-based backend.

[0144] Steps (i) to (vii) can be implemented by a controller 50 configured to receive input signal 58 and send output signal 60, wherein each of the input and output signals 58, 60 is one or both of command signal 62 and data signal 64.

[0145] According to another embodiment, a method 100 is provided for determining a corresponding connectivity score C for each of a plurality of geospatial tiles 13 in a geospatial dataset 19. Method 100 includes: (i) identifying the vehicle location L of a motor vehicle V1 using a controller 50. V1 (ii) Identifying one or more target geohash tiles 13t by using controller 50, wherein the one or more target geohash tiles 13t include one or more of the following: vehicle location L V1 (iii) At box 190, by using controller 50, receiving or accessing information 12 for each target geohash tile 13t, wherein information 12 refers to multiple parameters P affecting the connectivity between vehicle V1 and cloud-based backend 11; (iv) At box 200, by using controller 50, determining the corresponding connectivity score C for each target geohash tile 13t, wherein the connectivity score C is based on a weighted average of multiple parameters P; (v) At box 210, by using controller 50, determining which target geohash tiles 13t have a corresponding connectivity score C less than a minimum connectivity threshold C. min(vi) At box 220, each such target geohash tile 13t is defined as a dead zone DZ by using controller 50; (vii) At box 260, an action is performed by controller 50 based on DDTL, wherein the action includes one or more of the following: transmitting DDTL to vehicle V1, prefetching map data for the target geohash tile 13t, and causing a change in the operating state of vehicle V1.

[0146] According to yet another embodiment, a system 20 is provided for determining a corresponding connectivity score C for each of a plurality of regional metric tiles 14 in a geospatial dataset 19. System 20 includes: (i) a positioning module 28 configured to identify the vehicle location L of a motor vehicle V1. V1 (ii) Target module 30, configured to identify one or more target area measurement tiles 14t, the target area measurement tiles 14t including one or more of the following: vehicle location L V1 The current area measurement tile 14c in which the vehicle V1 is located, one or more surrounding area measurement tiles 14s directly surrounding the current area measurement tile 14c, and one or more upcoming area measurement tiles 14u that the vehicle V1 is expected to pass through; (iii) a receiving module 32, configured to receive or access information 12 of each target area measurement tile 14t related to multiple parameters P affecting the connectivity between the vehicle V1 and the cloud-based backend 11; (iv) a scoring module 34, configured to determine a corresponding connectivity score C for each target area measurement tile 14t based on a weighted average of the multiple parameters P; (v) a comparison module 36, configured to determine which target area measurement tiles 14t have a corresponding connectivity score C less than a minimum connectivity threshold C. minThus, each such target area measurement tile 14t is defined as a dead zone DZ; (vi) Adding module 38 is configured to add each dead zone DZ to a dynamic dead zone tile list DDTL; (vii) Execution module 44 is configured to perform actions based on DDTL, wherein the actions include one or more of the following: transmitting DDTL to vehicle V1, prefetching map data for the target area measurement tile 14t, and causing a change in the operating state of vehicle V1; (viii) Controller 50, together with positioning module 28, target module 30, and receiving... Module 32, scoring module 34, comparison module 36, addition module 38, and execution module 44 are operatively connected, wherein controller 50 is configured to: (a) receive input signal 46 from one or more of the positioning module 28, target module 30, receiving module 32, scoring module 34, comparison module 36, addition module 38, and execution module 44, and (b) send output signal 48 to one or more of the positioning module 28, target module 30, receiving module 32, scoring module 34, comparison module 36, addition module 38, and execution module 44.

[0147] System 20 may further include a detection module 22 configured to detect a handshake HS with the motor vehicle V1, wherein the controller 50 is also operatively connected to the detection module 22 and configured to receive one or both of an input signal 58 from the detection module 22 and send an output signal 60 to the detection module 22. Each of the input signal 58 and the output signal 60 may be one or both of a command signal 62 and a data signal 64.

[0148] DDTL can be hosted in a cloud-based backend.

[0149] For each target area metric tile 14t, the plurality of parameters P may include two or more of the following: cellular network signal strength P1, vehicle-reported signal quality / strength P2, weather-related signal interference P3, and signal obstacle impact P4. Each of parameters P1, P2, P3, and P4 may have corresponding weights w1, w2, w3, and w4, and the weighted average may be the sum of parameters P1, P2, P3, and P4 multiplied by their respective weights w1, w2, w3, and w4.

[0150] Although the individual steps of method 100 have been described as separate boxes, and the individual functions of system 20 have been described as separate modules or elements, it can be noted that two or more steps can be combined into fewer boxes, and two or more functions can be combined into fewer modules or elements. Similarly, some steps described as a single box can be divided into two or more boxes, and some functions described as a single module or element can be divided into two or more modules or elements. Furthermore, the order of the steps or boxes described herein can be rearranged in one or more different orders, and the arrangement of functions, modules, and elements can be rearranged into one or more different arrangements.

[0151] (As used herein, a “module” can include hardware and / or software, including executable instructions for receiving one or more inputs, processing one or more inputs, and providing one or more corresponding outputs. It should also be noted that at some points throughout this disclosure, a single input, output, element, etc., may be referred to, while at other points, a plurality of inputs, outputs, elements, etc., may be referred to. Therefore, no weight should be given to whether the terms “input,” “output,” “element,” etc., are used in singular or plural form at any particular point in this disclosure, as the singular and plural use of these terms should be considered interchangeable unless the specific context otherwise requires.)

[0152] The above description is intended to be illustrative and not restrictive. While the dimensions and types of materials described herein are intended to be illustrative, they are by no means restrictive and are exemplary embodiments. In the following claims, the terms “first,” “second,” “top,” “bottom,” etc., are used merely as labelling and are not intended to impose numerical or positional requirements on the objects thereto. For the purposes of this description, unless specifically stated otherwise, the use of the singular includes the plural, and vice versa. Furthermore, the phrases “at least one of A and B” and “A and / or B” should both be understood to mean “only A, only B, or both A and B.”

[0153] Furthermore, unless explicitly stated to the contrary, the words “comprising,” “containing,” “including,” “having,” etc., shall mean “including, but not limited to,” and embodiments that include one or more elements having a particular property may include one or more additional elements among such elements that do not have said property. And when broad descriptive adverbs such as “substantially” and “usually” are used herein to modify words or phrases, these adverbs mean “most,” “mainly,” “largely,” “significantly,” “to a great extent,” and / or “at least 51 to 99% of the 100% probable degree,” and do not necessarily mean “perfect,” “complete,” “strictly,” “complete,” or “100%.” Additionally, approximate words such as “approximately,” “almost,” “nearly,” or “approximately” may be used herein in the meaning of “at,” “close to,” or “almost at,” “within 0-5% of,” or “within acceptable manufacturing or production tolerances,” or logical combinations thereof. In addition, the word “close” in this article can be used to describe the position of an object or part of it relative to another object or part of it, and / or to describe the positional relationship between two objects or their respective parts relative to each other, and can mean “close to”, “near”, “close to”, “in the vicinity of”, “at a place of”, etc.

[0154] As used herein, a component or module "configured" to perform a specified function is capable of performing the specified function without alteration, rather than merely having the possibility of performing the specified function after further modification. In other words, the described component or module is specifically selected, created, implemented, utilized, programmed, and / or designed for the purpose of performing the specified function when explicitly configured to perform it.

[0155] This written description uses examples, including best practices, to enable those skilled in the art to manufacture and use devices, systems, and combinations of substances according to this disclosure, and to perform methods. The following claims include equivalents that define the scope of this disclosure.

Claims

1. A method for determining the corresponding connectivity score for each of multiple regional metric tiles in a geospatial dataset, comprising: (i) Identify the vehicle location of the motor vehicle; (ii) Identify one or more target area measurement tiles, the target area measurement tiles including one or more of the following: the current area measurement tile where the vehicle is located, one or more surrounding area measurement tiles directly around the current area measurement tile, and one or more upcoming area measurement tiles through which the vehicle is expected to travel. (iii) Receive or access information about each of the target area metric tiles relating to multiple parameters affecting the connectivity between the vehicle and the cloud-based backend; (iv) Determine the corresponding connectivity score for each of the target region metric tiles based on the weighted average of the plurality of parameters; (v) Determine which of the target region metric tiles have a corresponding connectivity score less than the minimum connectivity threshold, thereby defining each such target region metric tile as a dead zone; (vi) Add each dead zone to the Dynamic Dead Zone Tile List (DDTL); as well as (vii) Perform an action based on the DDTL, wherein the action includes one or more of the following: transmitting the DDTL to the motor vehicle, prefetching map data for the target area measuring tiles, and causing a change in the operating state of the motor vehicle.

2. The method according to claim 1, wherein, Each of the aforementioned region measurement tiles is an L5 geoscrambled tile.

3. The method of claim 1, wherein the plurality of regional metric tiles may comprise one or more large geohash tiles and one or more small geohash tiles, wherein each large geohash tile has a first geohash having a first number of alphanumeric characters, and each small geohash tile has a second geohash having a second number of alphanumeric characters greater than the first number.

4. The method according to claim 1, wherein, For each target area metric tile, the plurality of parameters includes two or more of the following: Cellular network signal strength; The vehicle reported the signal quality / strength; Weather-related signal interference; and Signal obstruction.

5. The method of claim 4, wherein each of the parameters has a corresponding weight, and wherein the weighted average is the sum of the parameters multiplied by their respective weights.

6. The method according to claim 5, wherein, For each target region metric tile, the connectivity score is represented by C, the parameters are represented by a first set {P1,P2,P3,P4}, and the weights are represented by a second set {w1,w2,w3,w4}, where C = (w1×P1) + (w2×P2) + (w3×P3) + (w4×P4).

7. The method according to claim 1, wherein, Each dead zone, along with its associated parameters, is stored in the DDTL.

8. The method according to claim 1, further comprising: Detect the handshake with the motor vehicle; The handshake occurs at the start of the key cycle of the motor vehicle.

9. The method according to claim 1, wherein, The change in the operating state includes at least one of the following: Take one or more actions aimed at increasing the corresponding connectivity score of the metric tiles in the target area; Change one or more conditions associated with the assisted driving mode; as well as Modify the scheduling for receiving downloads from the backend and sending uploads to the backend, or both.

10. The method according to claim 9, wherein, The actions taken include making route changes aimed at increasing one or more of the corresponding connectivity scores of the target area's metric tiles.

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