阅读说明：本技术 用于车辆定位的方法和系统 (Method and system for vehicle localization ) 是由 奥马尔·玛卡 奥列格·古西欣 于 2021-06-25 设计创作，主要内容包括：本文提供了用于车辆定位的方法和系统。一种示例性方法可包括获得操作区域内的地图。所述操作区域内的位置与一定样式的减速带相关联,所述样式的减速带被配置为当车辆行驶越过所述样式的减速带时产生来自所述车辆的车辆俯仰响应。所述方法可包括：从车辆传感器获得运动传感器信息；确定所述运动传感器信息与所述车辆俯仰响应何时匹配；以及当所述运动传感器信息对应于所述位置的所述车辆俯仰响应时,确定所述车辆在所述位置中。(Methods and systems for vehicle positioning are provided herein. An example method may include obtaining a map within an operating area. The location within the operating zone is associated with a pattern of speed bumps configured to generate a vehicle pitch response from the vehicle as the vehicle travels over the pattern of speed bumps. The method may comprise: obtaining motion sensor information from a vehicle sensor; determining when the motion sensor information matches the vehicle pitch response; and determining that the vehicle is in the location when the motion sensor information corresponds to the vehicle pitch response for the location.)

1. A method, the method comprising:

obtaining a map within an operating area, wherein locations within the operating area are associated with a pattern of speed bumps configured to generate a vehicle pitch response from a vehicle when the vehicle travels over the pattern of speed bumps;

obtaining motion sensor information from a vehicle sensor;

determining that the motion sensor information matches the vehicle pitch response; and

determining that the vehicle is in the location based on the vehicle pitch response for which the motion sensor information corresponds to the location.

2. The method of claim 1, wherein the pattern of speed bumps associated with the location comprises an asymmetric pattern, the method further comprising determining a direction of travel of the vehicle based on the motion sensor information.

3. The method of claim 1, wherein determining that the motion sensor information corresponds to the vehicle pitch response for the location comprises determining a velocity of the vehicle, wherein the motion sensor information from the vehicle is determined in conjunction with the velocity of the vehicle.

4. The method of claim 1, wherein determining that the motion sensor information corresponds to the vehicle pitch response for the location comprises:

transmitting the motion sensor information to a service provider; and

receiving location information from the service provider based on the service provider matching the motion sensor information to the vehicle pitch response for the location.

5. The method of claim 1, further comprising determining that the vehicle is within the operating region by detecting that the vehicle encounters a pattern of entry deceleration zones near an entry point of the operating region based on the motion sensor information.

6. The method of claim 1, further comprising navigating the vehicle through the operating zone based on previous navigation information when the vehicle does not encounter the patterned deceleration strip after driving within the operating zone for a period of time or after a predetermined distance.

7. The method of claim 1, wherein the motion sensor information comprises displacement of a vehicle suspension component.

8. A method, the method comprising:

obtaining a map of an operating area, the map identifying locations within the operating area, each of the locations identifiable using a pattern of deceleration strips that produce a vehicle pitch response by the vehicle as the vehicle travels over the pattern of deceleration strips;

converting motion sensor information of the vehicle into pitch data as the vehicle traverses the operating area; and

determining a position of the vehicle as corresponding to one of the positions based on the pitch data matching the vehicle pitch response of any of the positions.

9. The method of claim 8, further comprising determining that the vehicle is within the operating region.

10. The method of claim 8, wherein the pattern of speed bumps associated with a location comprises an asymmetric pattern, the method further comprising determining a direction of travel of the vehicle based on the motion sensor information.

11. The method of claim 8, further comprising determining a speed of the vehicle, wherein the motion sensor information from the vehicle is determined in conjunction with the speed of the vehicle.

12. The method of claim 8, further comprising:

transmitting the motion sensor information to a service provider; and

receiving location information from the service provider when the service provider matches the motion sensor information with the vehicle pitch response for the location.

13. The method of claim 8, further comprising navigating the vehicle through the operating zone based on previous navigation information when the vehicle does not encounter the patterned deceleration strip after driving within the operating zone for a period of time or after a predetermined distance.

14. The method of claim 8, wherein the motion sensor information comprises displacement of a vehicle suspension component.

15. A system, the system comprising: a processor; and

a memory to store instructions that are executed by the processor to:

obtaining motion sensor information from vehicle sensors when a vehicle encounters a speed bump within an operating region, wherein each location within the operating region is associated with a discrete pattern of speed bumps;

comparing the motion sensor information to a vehicle pitch response mapped to a location within the operating region; and

determining a current location of the vehicle.

Technical Field

The present disclosure relates generally to vehicle navigation.

Background

In areas where connectivity is reduced or absent, communication-enabled devices that provide location determination functionality may be adversely affected. For example, a mobile device or vehicle configured to determine its location from received Global Positioning Signal (GPS) information may be unable to determine its location when connectivity is impaired or absent.

Dead reckoning may be used whenever a device (such as a vehicle) relies on vehicle dynamics rather than GPS signals to estimate its position. GPS signal loss is very common in parking lots, which makes it difficult for vehicles to park autonomously (especially for autonomous valet parking applications). The autonomously parkable vehicle is not limited to an autonomous vehicle. For example, a driver-operated vehicle equipped with an Advanced Driver Assistance System (ADAS) may also park autonomously.

In an exemplary use case, a communication device within the parking lot may transmit a location signal to the vehicle. Once a car enters a parking lot and the GPS signal is lost, the vehicle must accurately estimate its position in order to be able to turn or activate an automatic parking system when needed, which may require knowledge of the infrastructure.

Disclosure of Invention

The present disclosure relates to methods and systems that allow a vehicle to determine the location of the vehicle in areas where communication capabilities are reduced or unavailable. In general, the present disclosure may relate to the use of speed bumps provided in an operating area. The speed bumps may be arranged in a discrete or unique pattern that allows the speed bumps to be used to identify specific locations within the operating field. Unique patterns can be created by selecting the spacing between adjacent speed bumps, changing the geometric differences between adjacent speed bumps, or a combination thereof.

As an example, the location within the garage may be identified by a pattern of speed bumps, such as three speed bumps. In one example, the first speed bump may be spaced two feet from the second speed bump, and the second speed bump may be spaced four feet from the third speed bump. An entrance to a particular level of the parking garage can be identified by a first deceleration strip that is two feet in width, followed by a second deceleration strip that is three feet in width, where the first and second deceleration strips are spaced apart by a distance of two feet. In yet another example, the height of the speed bump may also be used as a distinguishing aspect. For example, a first speed bump may have a height of three inches, while a second speed bump may have a height of seven inches. This difference in deceleration strip height between two or more deceleration strips may result in a unique vehicle pitch response that is different from a pattern of deceleration strips that is different from two otherwise similar deceleration strips having the same or similar height relative to each other.

In summary, the vehicle may encounter some of these unique versions of the speed bump as the vehicle traverses within the operating area. When the vehicle is driven over a uniquely patterned deceleration strip, a corresponding vehicle pitch response occurs. Generally, when a vehicle traverses a unique model of a speed bump, the vehicle may experience a change in pitch (e.g., yaw or movement upward). These pitch responses may be identified by monitoring motion sensing elements (such as accelerometers, etc.) on the vehicle. The pitch response may be determined by measuring the deflection of a vehicle suspension component, such as the stroke of a shock absorber or the deflection of a leaf spring, etc. The pitch response may be measured and converted to a measured vehicle pitch response.

The vehicle may include a controller that may use a map to determine the vehicle location. The map identifies specific locations within the operating area, and each of these locations is associated with a unique pattern of speed bumps. Each unique pattern of speed bumps may be associated with an expected vehicle pitch response. That is, the map correlates expected vehicle pitch response to location. The vehicle may determine its position by comparing the motion sensor signal to these expected vehicle pitch responses. When the motion sensor signal corresponds to one of the expected vehicle pitch responses, the vehicle may confirm its location in the operating region. The vehicle may also use the locating features in conjunction with vehicle speed to estimate its position.

It should be understood that the vehicle may alternatively determine its position by communicating with an infrastructure device (e.g., a service provider) configured to perform the vehicle positioning signal comparison process described above. The systems and methods herein may be configured to allow a vehicle to infer its direction of travel based on deceleration strip interaction and/or to navigate an operating area based on a priori knowledge when deceleration strip interaction cannot be determined.

Drawings

The detailed description explains the embodiments with reference to the drawings. The use of the same reference numbers may indicate similar or identical items. Various embodiments may utilize elements and/or components other than those shown in the figures, and some elements and/or components may not be present in various embodiments. Elements and/or components in the drawings have not necessarily been drawn to scale. Throughout this disclosure, depending on the context, singular and plural terms may be used interchangeably.

FIG. 1 depicts an illustrative architecture in which techniques and structures for providing the systems and methods disclosed herein may be implemented.

FIG. 2 illustrates an exemplary unique pattern of speed bumps associated with the exemplary expected vehicle pitch response graph shown.

Fig. 3 shows various speed bump style configurations.

Fig. 4 is a flow chart of an exemplary method of the present disclosure.

Fig. 5 is a flow chart of another exemplary method of the present disclosure.

Fig. 6 is a flow chart of yet another exemplary method of the present disclosure.

Detailed Description

Turning now to the drawings, FIG. 1 depicts an illustrative architecture 100 in which the techniques and structures of the present disclosure may be implemented. Architecture 100 may include an operating area 102, a vehicle 104, and a service provider 106. The vehicle 104 may communicate with the service provider 106 over a network 108. The network 108 may include any one or combination of a number of different types of networks, such as a wired network, the internet, a wireless network, and other private and/or public networks. In some cases, the network 108 may include a cellular network, Wi-Fi, or Wi-Fi direct. As described above, the vehicle 104 may be adapted to directly perform vehicle localization, and in some cases, vehicle localization may be a collaborative effort between the vehicle 104 and the service provider 106, as will be discussed in more detail.

Operating area 102 may include a parking garage, but it should be understood that operating area 102 may include any area in which vehicles may operate in accordance with the present disclosure. In some use cases, the operating area 102 is shown as a map 121, as will be discussed in more detail. The systems and methods disclosed herein allow the vehicle 104 to determine its location in locations where connectivity is poor or unavailable. While some of these locations will include a parking garage as an example, the present disclosure is not so limited and may be used to enable object positioning in any location where connectivity is reduced or unavailable. For example, parking facilities in remote rural areas may be located in areas where connectivity is reduced or absent.

An exemplary configuration of operating area 102 may include a floor 110 of a parking garage. The floor 110 may include a plurality of locations, each of which may be associated with a pattern of speed bumps. For example, an entrance ramp 111 (an exemplary location) to the floor 110 may be associated with a first unique style of speed bump 112. Another area of the floor 110 may be associated with a second unique pattern of speed bumps 114. Reserved parking space 113 may be identified using a second unique pattern of speed bumps 114. Again, these are merely examples of how operating regions may be configured with unique patterns of deceleration strips in accordance with the present disclosure and are not intended to be limiting. The operating area 102 may include a unique set of entry speed bumps 118 that indicate to the vehicle 104 that it has entered the operating area 102.

Generally, a unique pattern of speed bumps is associated with a particular/discrete location in the operational area 102. The unique pattern of speed bumps is intended to produce a vehicle pitch response (upward movement of the vehicle) as the vehicle 104 drives over the unique pattern of speed bumps. As shown in fig. 2, first unique pattern of speed bumps 112 includes speed bumps 120A, 120B, and 120C. First speed bump 120A is spaced apart from second speed bump 120B by a distance D1, and distance D1 is smaller than distance D2 between second speed bump 120B and third speed bump 120C. Through empirical measurements, it should be appreciated that an expected vehicle pitch response may result when vehicle 104 is driven past speed bumps 120A, 120B, and 120C at a particular speed (which may be associated with a speed limit within a parking garage, such as ten miles per hour). The expected vehicle pitch response is graphically represented in graph 122. Graph 122 includes pitch change regions 124A, 124B, and 124C that correspond to the observed changes in pitch of vehicle 104 that should be sensed by the vehicle's motion sensors as vehicle 104 drives across speed bumps 120A, 120B, and 120C. It should be understood that these deceleration strip patterns are not intended to be limiting in nature, but are provided as exemplary patterns only.

A map 121 of the operating area 102 may be created, where particular locations within the operating area 102 are associated with expected vehicle pitch responses. The location may be associated with a deceleration strip that produces a unique pattern of expected vehicle pitch response. Some of the operational areas 102 are provided with speed bumps that are not arranged in a unique pattern, but are arranged in a repeatable pattern, such as speed bump grouping 127 (three evenly spaced speed bumps). For example, the spaces between locations may be provided with a repeating pattern of speed bumps. Regions of repeating patterns of speed bumps may exist between first unique pattern of speed bump 112 and second unique pattern of speed bump 114, and between second unique pattern of speed bump 114 and third unique pattern of speed bump 116. Although the map 121 has been shown for purposes of description, the map 121 may also be represented as a data structure, such as a table or record. The repeatable pattern may be used to provide general feedback to the vehicle that the vehicle is traveling between identifiable locations, but the vehicle 104 is typically traveling in a designated or acceptable portion of the operating region 102. For example, sensing of the repeatable pattern by the vehicle 104 may indicate that the vehicle 104 is not deviating from operation in a safe driving area or lane.

Referring collectively to fig. 1 and 2, in addition to correlating location with expected vehicle pitch response, location may also be correlated with location information, such as GPS coordinates. Alternatively, the location may be identified by name or may be identified as a general section of the operating region 102.

A location map of the operating area may be created that associates vehicle pitch responses with their respective locations and unique patterns of speed bumps. In general or in particular, GPS coordinates may be used to identify a location. The maps of the present disclosure may be used at the vehicle level or the service provider level.

The vehicle 104 may include a controller 128, which in turn includes a processor 130 and a memory 132. The memory 132 stores instructions that are executed by the processor 130 to perform various aspects of vehicle positioning and navigation, as disclosed throughout. When referring to operations performed by the controller 128, it will be understood that this includes execution of instructions by the processor 130.

The controller 128 may be configured to obtain pitch data from one or more motion sensors. For example, the vehicle 104 may include an accelerometer 134 associated with the body. The accelerometer 134 generates motion sensor information when the vehicle 104 is operating within the operating region 102. As the vehicle 104 traverses, the controller 128 may process the motion sensor information generated by the accelerometer 134 to determine vehicle pitch response data. The controller 128 may be configured to process the motion sensor information using machine learning and/or artificial intelligence techniques. For example, the controller 128 may utilize a recurrent neural network to process the motion sensor information and detect the signal pattern in a time series. The controller 128 processes the motion sensor information to create a measured vehicle pitch response. This measured vehicle pitch response may be represented as a graph in a format similar to graph 122 of fig. 2. Further, while pitch data may be determined from motion sensor information, measured vehicle pitch responses (e.g., pitch data) may also be determined from displacement of the vehicle suspension component 142. For example, the travel of the shock absorbers of the vehicle 104 may be measured, quantified, and converted into a measured vehicle pitch response.

Once the motion sensor information has been processed to create a measured vehicle pitch response, the controller 128 may compare the measured vehicle pitch response to an expected vehicle pitch response included in the map 121 provided to the vehicle 104. If the controller 128 can determine a match (fuzzy or accurate), the vehicle 104 can determine its position according to the matching process. As mentioned above, the position of the vehicle may be understood as a general location within the operating area 102, or a more specific fine location identified by specific geophysical coordinates associated with the location and built into the map 121.

If the vehicle 104 is moving during this positioning process, information from the telematics control unit 136 of the vehicle 104 can be used to determine the current vehicle speed and determine the estimated location of the vehicle 104 based on the last known location of the vehicle when the vehicle 104 passed the location on the map 121. This type of estimated position may be displayed on a human machine interface (HMI 138) of the vehicle 104. For example, the navigation feature may display a representation of a map 121 on which the estimated vehicle location is displayed. The estimated position may be determined by the controller 128 using dead reckoning techniques that are informed and enhanced by the positioning process disclosed herein.

In addition to positioning, the controller 128 may interpret the deceleration strip pattern to infer the direction of travel of the vehicle 104. This may allow for the direction of travel to be inferred when the speed bumps are arranged in a non-linear pattern, such as the first unique pattern of speed bumps 112 with irregular spacing between adjacent speed bump pairs. For example, when vehicle 104 is traveling from left to right across the first unique pattern of speed bump 112, the measured vehicle pitch response generated by controller 128 is different than the measured vehicle pitch response generated by controller 128 when vehicle 104 is traveling from right to left across the first unique pattern of speed bump 112.

While some of the above embodiments contemplate vehicle positioning and navigation being performed at the vehicle level, vehicle positioning and navigation may also be performed cooperatively between the controller 128 and the service provider 106. For example, the service provider 106 may be configured with a location service 140 that receives motion sensor information from the vehicle 104 over the network 108. The service provider 106 may use the location service 140 to compare the motion sensor information (e.g., measured vehicle pitch response) to expected vehicle pitch responses for the location of the operating region 102 and determine whether there is a match. If there is a match, the location service 140 may identify the location and send location information associated with the location back to the vehicle 104 for navigational guidance and/or display of the location. As described above, the position information and vehicle speed information obtained from the telematics control unit 136 may be used in combination to provide a vehicle position estimate while the vehicle is traveling. Assuming clock synchronization between the service provider 106 and the controller 128 of the vehicle 104, the service provider 106 may also use the slave telematics control unit 136 in conjunction with the positioning information to estimate the estimated position of the moving vehicle. The service provider 106 may be installed as an infrastructure device near or within an operating area.

Vehicle positioning and navigation may also be performed cooperatively between the controller 128, the service provider 106, and/or the speed bump. For example, the speed bumps may be "smart" speed bumps connected to a network. In other cases, the speed bump may communicate directly with the vehicle.

In some embodiments, the speed bump may include one or more energy harvesting devices that harvest energy from a vehicle passing through the speed bump. For example, as the vehicle is raised and lowered over the speed bump, the speed bump may cause a change in the potential energy of the vehicle around the speed bump. This potential energy can be captured by the deceleration strip. For example, energy from the motion and weight of a vehicle passing through a speed bump may be collected by various mechanisms, including the use of piezoelectric materials, springs with magnets and coils, or any other known mechanism. The speed bump may include an energy storage device (such as a capacitor or battery) that allows the speed bump to store excess energy. In this way, the speed bump can be powered for a long time.

As described above, the vehicle may communicate directly with the speed bump. In this mode, the energy consumption of the intelligent speed bump may be reduced due to the reduced signal range. The speed bump may only need to communicate with the vehicle on top of it, and the vehicle knows to look for local signals (such as bluetooth low energy, etc.) because the vehicle's accelerometer may detect the bump. In other cases, the speed bump sensors may be in communication with the infrastructure. For example, the vehicle may detect a speed bump and send a signal to the service provider indicating that a speed bump is detected. In such cases, the speed bump may also send trigger information to the service provider. The service provider can match each bump to a vehicle for location purposes.

Fig. 3 illustrates some example speed bump patterns or configurations that may be used in accordance with the present disclosure. Speed bump pattern 302 includes two speed bumps having different width dimensions. For example, speed bump 304 has a width W1 that is greater than a width W2 of an adjacent speed bump 306. Also shown is an expected vehicle pitch response graph 308 for the deceleration strip pattern 304. When the vehicle passes through the deceleration strip from right to left, the pitch amplitude is determined according to the accelerometer signal. It is assumed that all jounce starts such that the front wheel contact occurs before the rear wheel contact.

Another example speed bump pattern 312 is shown in plan view or side view. Speed bump pattern 312 includes two speed bumps having different height dimensions. For example, height dimension HI of speed bump 314 is less than height dimension H2 of adjacent speed bump 316. The retarder may have unique height and width dimensions that will produce a particular characteristic or vehicle pitch response that may be detected using, for example, a recurrent neural network. The recurrent neural network may be trained to identify a particular deceleration strip pattern and its expected vehicle pitch response, and to provide a match between the measured vehicle pitch response (e.g., motion sensor information) and the expected vehicle pitch response.

Referring back to fig. 1, in some cases, if the controller 128 determines that the vehicle has not encountered any speed bumps after entering the operating area of the present disclosure, the controller 128 may default to relying on previous navigation information to navigate the vehicle through the operating area. This previous navigation information may be used when the vehicle has not encountered a speed bump after traveling within the operating area for a certain period of time or after a predetermined distance. The predetermined distance may be measured from a pattern of entrance deceleration strips near the entrance point of the operating region. Previous navigation information may be collected from previous instances in which the vehicle (or other vehicle) has driven through the operating area. The controller 128 may also be configured to feed vehicle operation information such as position and location determinations back into the previous navigation information to improve and update the logic. The controller 128 may utilize previous navigation information when motion sensor information or measured vehicle pitch responses are not available or when they fail to match expected vehicle pitch responses.

Fig. 4 is a flow chart of an exemplary method of the present disclosure. The method includes a step 402 of obtaining a map within an operational area. As described above, the location may be one of many locations within the operating region. Each of the positions may be associated with a pattern of speed bumps configured to generate a vehicle pitch response from the vehicle as the vehicle travels over the pattern of speed bumps.

Next, the method may include a step 404 of obtaining motion sensor information from a vehicle sensor (such as an accelerometer or a suspension component of the vehicle). The method may include a step 406 of determining when the motion sensor information matches the vehicle pitch response. The motion sensor information may be used to determine a measured vehicle pitch response, and the measured vehicle pitch response may be matched to an expected vehicle pitch response (collectively referred to above as vehicle pitch responses).

The method can include the step 408 of determining that the vehicle is at the location when the motion sensor information corresponds to the vehicle pitch response for the location. In the method, the step of obtaining a map (step 402) may include a controller of the vehicle obtaining the map or a service provider loading the map. When a service provider is involved, the method may comprise steps relating to: transmitting the motion sensor information to a service provider; and receiving location information from the service provider when the service provider matches the motion sensor information with the vehicle pitch response for the location.

Fig. 5 is a flow chart of another exemplary method of the present disclosure. The method may include a step 502 of obtaining a map within an operating area. The map may identify a location within the operational area. As noted above, each of the positions may be uniquely identified using a pattern of speed bumps that generate a vehicle pitch response by the vehicle as the vehicle travels over the pattern of speed bumps. The method includes a step 504 of converting motion sensor information of the vehicle into pitch data as the vehicle traverses the operating area, and a step 506 of determining the location of the vehicle as corresponding to one of the locations when the pitch data matches the vehicle pitch response of any of the locations.

Fig. 6 is another exemplary method of the present disclosure. The method includes a step 602 of obtaining motion sensor information from vehicle sensors when a vehicle encounters a speed bump in an operating area. Next, the method may include a step 604 of determining a current location of the vehicle. In some cases, the current location of the vehicle may be determined using the motion sensor information and the vehicle speed. Accordingly, the process of determining the current position of the vehicle may further include the step 606 of comparing the motion sensor information to the vehicle pitch response mapped to a position within the operating region. Each of the positions may be associated with a discrete pattern of speed bumps. The current position may also be determined by the step 608 of obtaining the speed of the vehicle. Both motion sensor information and vehicle speed may be used together to determine the current location of the vehicle.

In the foregoing disclosure, reference has been made to the accompanying drawings that form a part hereof, and in which is shown by way of illustration specific embodiments in which the disclosure may be practiced. It is to be understood that other embodiments may be utilized and structural changes may be made without departing from the scope of the present disclosure. References in the specification to "one embodiment," "an example embodiment," etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it will be recognized by one skilled in the art that such feature, structure, or characteristic may be used in connection with other embodiments whether or not explicitly described.

Embodiments of the systems, apparatus, devices, and methods disclosed herein may comprise or utilize a special purpose or general-purpose computer including computer hardware, such as, for example, one or more processors and system memory, as discussed herein. Implementations within the scope of the present disclosure may also include physical and other computer-readable media for carrying or storing computer-executable instructions and/or data structures. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer system. Computer-readable media storing computer-executable instructions are computer storage media (devices). Computer-readable media carrying computer-executable instructions are transmission media. Thus, by way of example, and not limitation, embodiments of the present disclosure can include at least two distinct computer-readable media: computer storage media (devices) and transmission media.

Computer storage media (devices) includes RAM, ROM, EEPROM, CD-ROM, Solid State Drives (SSDs) (e.g., based on RAM), flash memory, Phase Change Memory (PCM), other types of memory, other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.

Embodiments of the apparatus, systems, and methods disclosed herein may communicate over a computer network. A "network" is defined as one or more data links that enable the transfer of electronic data between computer systems and/or modules and/or other electronic devices. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or any combination of hardwired or wireless) to a computer, the computer properly views the connection as a transmission medium. Transmission media can include a network and/or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media.

Computer-executable instructions comprise, for example, instructions and data which, when executed at a processor, cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. The computer-executable instructions may be, for example, binary code, intermediate format instructions (such as assembly language), or even source code. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the features or acts described above. Rather, the described features and acts are disclosed as example forms of implementing the claims.

Those skilled in the art will appreciate that the disclosure may be practiced in network computing environments with many types of computer system configurations, including internal vehicle computers, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, tablet computers, pagers, routers, switches, various storage devices, and the like. The present disclosure may also be practiced in distributed system environments where tasks are performed by local and remote computer systems that are linked (either by hardwired data links, wireless data links, or by any combination of hardwired and wireless data links) through a network. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

Further, where appropriate, the functions described herein may be performed in one or more of the following: hardware, software, firmware, digital components, or analog components. For example, one or more Application Specific Integrated Circuits (ASICs), for example, can be programmed to perform one or more of the systems and procedures described herein. Certain terms are used throughout the description and claims to refer to particular system components. As one skilled in the art will appreciate, components may be referred to by different names. This document does not intend to distinguish between components that differ in name but not function.

It should be noted that the sensor embodiments discussed above may include computer hardware, software, firmware, or any combination thereof to perform at least a portion of their functions. For example, the sensor may include computer code configured to be executed in one or more processors and may include hardware logic/circuitry controlled by the computer code. These exemplary devices are provided herein for illustrative purposes and are not intended to be limiting. As known to those skilled in the relevant art, embodiments of the present disclosure may be implemented in other types of devices.

At least some embodiments of the present disclosure have been directed to computer program products comprising such logic (e.g., in the form of software) stored on any computer usable medium. Such software, when executed in one or more data processing devices, causes the devices to operate as described herein.

While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be apparent to persons skilled in the relevant art that various changes in form and detail can be made therein without departing from the spirit and scope of the disclosure. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents. The foregoing description has been presented for purposes of illustration and description. The foregoing description is not intended to be exhaustive or to limit the disclosure to the precise form disclosed. Many modifications and variations are possible in light of the above teaching. Further, it should be noted that any or all of the foregoing alternative embodiments may be used in any desired combination to form additional hybrid embodiments of the present disclosure. For example, any of the functions described with respect to a particular device or component may be performed by another device or component. Further, although particular device features have been described, embodiments of the present disclosure may be directed to many other device features. Furthermore, although embodiments have been described in language specific to structural features and/or methodological acts, it is to be understood that the disclosure is not necessarily limited to the specific features or acts described. Rather, the specific features and acts are disclosed as illustrative forms of implementing the embodiments. Conditional language, such as particularly "may," "may," or "may" is generally intended to convey that certain embodiments may include certain features, elements, and/or steps, while other embodiments may not include certain features, elements, and/or steps, unless specifically stated otherwise or otherwise understood within the context when used. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments.

According to one embodiment of the invention, the invention also features a service provider configured to compare the motion sensor information to a vehicle pitch response mapped to a location within an operating region.

According to an embodiment, the processor is configured to transmit the motion sensor information to the service provider and receive the current location from the service provider.

According to an embodiment, the processor is configured to navigate the vehicle through the operating area when determining the current location over time.

According to an embodiment, the processor is configured to navigate the vehicle through the operating area based on previous navigation information when the vehicle does not encounter a speed bump after driving within the operating area for a certain period of time or after a predetermined distance.

According to an embodiment, the processor is configured to periodically update the previous navigation information with the motion sensor information and the current location of the vehicle as the current location changes over time while the vehicle is within the operating area.