GB2616412A

GB2616412A - System and apparatus suitable for improving positional data accuracy, and a processing method in association thereto

Info

Publication number: GB2616412A
Application number: GB2202845.0A
Authority: GB
Inventors: Singh Brajraj; Subbaian Sudhagar; Mukhopadhyay Shilpa
Original assignee: Continental Automotive Technologies GmbH
Current assignee: Continental Automotive Technologies GmbH
Priority date: 2022-03-02
Filing date: 2022-03-02
Publication date: 2023-09-13
Also published as: WO2023165860A1; GB202202845D0

Abstract

There is provided a processing method in association with a vehicle. The processing method can include a receiving step and a processing step. The receiving step can include receiving at least one input signal. The input signal(s) can include vehicle data indicative of path of travel of the vehicle and positional data. The processing step can include processing the received input signal(s) to generate at least one output signal. Based on the vehicle data, when path of travel of the vehicle is determined to be circular, the input signal is processable in a manner such that the output signal is indicative that vehicle coordinates associated with the vehicle correspond to the positional data. Based on the vehicle data, when path of travel of the vehicle is determined to be non-circular, the input signal is processable by manner of adjustment-based processing to produce at least one output signal corresponding to adjusted positional data.

Description

SYSTEM AND APPARATUS SUITABLE FOR IMPROVING POSITIONAL DATA ACCURACY, AND A PROCESSING METHOD IN ASSOCIATION THERETO

Field Of Invention

The present disclosure generally relates to one or both of a system and an apparatus suitable for improving accuracy of positional data in relation to, for example, a vehicle. The present disclosure further relates a processing method associable to the system and/or the apparatus.

Background

Generally, location (i.e., position) of, for example, a vehicle (e.g., a car, an aircraft or a watercraft) can be determined by use of a global navigation satellite system (GNSS). Global Positioning Systems (GPS) is an example of a type of GNSS.

However, error(s) from a GNSS (e.g., GPS) should not be considered uncommon.

Error(s) can, for example, be due to factors such as: * Drifting time data from satellite clock * Ionosphere signal delay and deflection * Lower stability of receiver clock as compared to satellite clocks * Introduction of error during receipt of satellite orbit data by a GPS receiver module * Lower atmosphere signal delay (e.g., troposphere, tropopause and/or stratosphere) * Multipath errors Appreciably, such error(s) can compromise reliability/accuracy of data regarding the location (i.e., position) of a vehicle.

The present disclosure contemplates that there is a need to improve accuracy/reliability of data obtained from, for example, a GNSS.

Summary of the Invention

In accordance with an aspect of the disclosure, there is provided an apparatus which can, for example, be suitable for improving accuracy of positional data in relation to, for example, a vehicle.

Generally, the apparatus can be suitable for use in association with a vehicle, in accordance with an embodiment of the disclosure. The apparatus can, in one embodiment, include a first module and a second module. The first and second modules can be coupled.

The first module can be configured to receive at least one input signal and the second module can be configured the input signal(s) to produce at least one output signal.

The input signal(s) can include vehicle data and positional data.

Vehicle data can be communicated from at least one sensor (e.g., which can be carried by one or both of the vehicle and the apparatus). The sensor(s) can be coupled to the first module. Moreover, vehicle data can be indicative of whether path of travel of the vehicle is either circular or non-circular (e.g., a straight-lined path of travel).

Positional data can be communicated from at least one device coupled to the apparatus. Furthermore, the positional data can, for example, include longitude data and latitude data in association with the vehicle, in accordance with an embodiment of the disclosure. Additionally, in one example, the positional data can correspond to global positioning system (GPS) based vehicle data, in accordance with an embodiment of the disclosure.

Based on the vehicle data, when path of travel of the vehicle can be determined to be circular, the input signal(s) can be processed in a manner such that the output signal(s) can be indicative that vehicle coordinates associated with the vehicle correspond to the positional data.

Moreover, based on the vehicle data, when path of travel of the vehicle can be determined to be non-circular, the input signal(s) can be processed by manner of adjustment-based processing to produce at least one output signal corresponding to adjusted positional data. In one embodiment, adjustment-based processing can, for example, be by manner of processing the input signal(s) based on at least one adjustment factor which can include at least one correction parameter. For example, adjustment-based processing can be by manner of processing the input signal(s) based on at least a first adjustment factor (which can include at least one correction parameter) and a second adjustment factor (which can include at least one correction parameter), the first adjustment factor and the second adjustment factor being different. In a more specific example, adjustment-based processing can be by manner of processing latitude data based on a first adjustment factor and processing longitude data based on a second adjustment factor.

In one embodiment, the apparatus can, for example, further include a fourth module which can correspond to a prediction module. The prediction module can, for example, be configured to receive and further process the output signal(s) to generate at least one prediction signal. The output signal can, for example, be processed by manner of prediction-based processing to generate at least one prediction signal which can be communicated to the first module. The first module can, in turn, communicate (i.e., also referrable to as forward communication in this context) the prediction signal(s) to the second module for further processing. In this regard, it is appreciable that the second module can, for example, be configured to generate the output signal(s) based on the input signal(s) and the one prediction signal(s), in accordance with an embodiment of the disclosure.

It is appreciable that the present disclosure generally contemplates that in the above manner, accuracy of positional data communicated from, for example, a GNSS can possibly be improved. By taking into account vehicle heading data and distinguishing between circular and non-circular path of travel for the purpose of generating the output signal(s) in the above discussed manner, accuracy of positional data communicated from, for example, a GNSS can be improved. Thus it is possible that more accurate information concerning vehicle coordinates can be facilitated. Appreciably, the present disclosure contemplates using (comparatively) less-accurate positional data (as communicated from, for example, a GNSS) in conjunction with the latest (e.g., updated or real-time) vehicle heading data to possibly mitigate one or more errors associated with positional data so as to improve accuracy of received positional data.

Moreover, by manner of the above discussed processing (e.g., manner of processing based on a distinction as between whether path of travel is circular or non-circular), the present disclosure contemplates that complicated computations (i.e., processing) which may require significant processing resources can possibly be unnecessary. Specifically, in the above manner, accuracy of received positional data can possibly be facilitated in a more efficient manner (i.e., possibly a more efficient manner of processing for possible improvement in accuracy of received positional data).

Furthermore, by manner of the above discussed prediction-based processing, reliability integrity and/or robustness can be facilitated as, in addition, to positional data, prediction data can be utilized for computation (i.e., processing).

The above-described advantageous aspect(s) of the apparatus of the present disclosure can also apply analogously (all) the aspect(s) of a below described processing method of the present disclosure. Likewise, all below described advantageous aspect(s) of the processing method of the disclosure can also apply analogously (all) the aspect(s) of above described apparatus of the disclosure.

In accordance with another aspect of the disclosure, there is provided a processing method which can be suitable for improving accuracy of positional data in relation to, for example, a vehicle (not shown).

Generally, the processing method can be in association with a vehicle. The processing method can include a receiving step and a processing step, in accordance with an embodiment of the disclosure. In one embodiment, the processing method can further include an output generating step.

The receiving step can include receiving at least one input signal. In one embodiment, the input signal(s) can be received by, for example, the first module of the earlier mentioned apparatus. The input signal(s) can include vehicle data indicative of path of travel of the vehicle and positional data. The vehicle data can be communicated from at least one sensor (e.g., which can be carried by the vehicle and/or the apparatus), in accordance with an embodiment of the disclosure. Moreover, the positional data can be communicated from the earlier mentioned device.

The processing step can include processing the received input signal(s) to generate at least one output signal. The input signal(s) can be processed by the second module of the earlier mentioned apparatus.

Based on the vehicle data, when path of travel of the vehicle can be determined to be circular, the input signal(s) can be processed in a manner such that the output signal(s) can be indicative that vehicle coordinates associated with the vehicle can correspond to the positional data.

Moreover, based on the vehicle data, when path of travel of the vehicle can be determined to be non-circular, the input signal(s) can be processed by manner of adjustment-based processing to produce at least one output signal corresponding to adjusted positional data.

In one embodiment, the processing method can further include receiving at least one prediction signal for further processing to generate at least one output signal. The prediction signal(s) can, for example, be generated by the fourth module (e.g., the prediction module) of the earlier mentioned apparatus. In one example, the fourth module can, for example, be configured to receive and further process the output signal(s) to generate at least one prediction signal. The output signal(s) can, for example, be processed by manner of prediction-based processing to generate at least one prediction signal, in accordance with an embodiment of the disclosure.

The present disclosure further contemplates a computer program (not shown) which can include instructions which, when the program is executed by a computer (not shown), cause the computer to carry out any one of, or any combination of, the receiving step, the processing step and the output generating step, as discussed with reference to the processing method.

The present disclosure yet further contemplates a computer readable storage medium (not shown) having data stored therein representing software executable by a computer (not shown), the software including instructions, when executed by the computer, to carry out any one of, or any combination of, the receiving step, the processing step and the output generating step, as discussed with reference to the processing method.

As mentioned earlier, in the above manner, accuracy of positional data communicated from, for example, a GNSS can possibly be improved. Moreover, in the above manner, accuracy of received positional data can possibly be facilitated in a more efficient manner (i.e., possibly a more efficient manner of processing for possible improvement in accuracy of received positional data). Furthermore, by manner of the above discussed prediction-based processing, reliability integrity and/or robustness can be facilitated as, in addition, to positional data, prediction data can be utilized for computation (i.e., processing).

Brief Description of the Drawings

Embodiments of the disclosure are described hereinafter with reference to the following drawings, in which: Fig. 1 shows a system which can include at least one apparatus, according to an embodiment of the disclosure; Fig, 2 shows the apparatus of Fig, 1 in further detail, according to an embodiment of

the disclosure;

Fig. 3 shows a processing method in association with the system of Fig. 1, according to an embodiment of the disclosure; Fig. 4a and Fig. 4b show, respectively, a first example flow diagram and a second flow diagram in association with the processing method of Fig. 3, according to an

embodiment of the disclosure;

Fig. 4c shows a first example case in association with the first example flow diagram of Fig. 4a, in accordance with an embodiment of the disclosure; Fig. 4d shows a second example case in association with the second example flow diagram of Fig. 4b, in accordance with an embodiment of the disclosure; and Fig. 5 shows an example detection/determination flow diagram concerning path of travel of a vehicle, in association with the first and second example flow diagrams of Fig. 4a and Fig. 4b, according to an embodiment of the disclosure.

Detailed Description

The present disclosure contemplates that to improve data accuracy from, for example, a Global Navigation Satellite System (GNSS) such as a Global Positioning System (GPS) in association with, for example, a vehicle, it can be helpful to utilize data concerning heading of the vehicle (i.e., vehicle heading data).

Vehicle heading data can relate to compass direction in which the front end (e.g., a grille) of the vehicle is pointed.

The present disclosure contemplates that it is possible to perform adjustment-based processing and/or filtering-based processing in connection with the vehicle heading data based on, for example, whether the vehicle is traveling in a non-circular (e.g., straight-line) direction or in a circular direction. In this regard, the present disclosure further contemplates that it may be helpful to determine whether a vehicle is being operated (e.g., driven) in a manner so as to travel in a circular direction or not (i.e., traveling in straight-line direction instead of a circular direction).

The foregoing will be discussed in further detail with reference to Fig. 1 to Fig. 5 hereinafter.

Referring to Fig. 1, a system 100 is shown, according to an embodiment of the disclosure. The system 100 can be suitable for improving accuracy of positional data in relation to, for example, a vehicle (not shown). Specifically, the system 100 can be suitable for improving accuracy positional data (e.g., in relation to a vehicle) communicated from a GNSS.

The system 100 can include one or more apparatuses 102, at least one device 104 and a communication network 106, in accordance with an embodiment of the disclosure. In one embodiment, the system 100 can further include, as an option, one or more host devices (not shown).

The apparatus(es) 102 can be coupled to the device(s) 104. Specifically, the apparatus(es) 102 can, for example, be coupled to the device(s) 104 via the communication network 106. The host device(s) can, for example, be coupled to one or both of the apparatus(es) 102 and the device(s) 104. Specifically, the host device(s) can, for example, be coupled to the apparatus(es) 102 and/or the device(s) 104 via the communication network 106.

In one embodiment, the apparatus(es) 102 can be coupled to the communication network 106 and the device(s) 104 can be coupled to the communication network 106. Moreover, in one embodiment, the host device(s) can be coupled to the communication network 106. Coupling can be by manner of one or both of wired coupling and wireless coupling.

The apparatus(es) 102 can, in general, be configured to communicate with the device(s) 104 via the communication network 106, according to an embodiment of the disclosure. The host device(s) can, in general, be configured to communicate with the apparatus(es) 102 and/or the device(s) 104 via the communication network 106, according to an embodiment of the disclosure.

The apparatus(es) 102 can, for example, correspond to one or more computers (e.g., an electronic device/module having computing capabilities such as an electronic mobile device which can be carried into a vehicle or an electronic module which can be installed in a vehicle). Generally, the apparatus(es) 102 can, in one embodiment, be configured to perform one or more processing tasks. As a general example, the apparatus(es) 102 can be configured to receive one or more input signals and process the input signal(s) in a manner so as to produce one or more output signals. The apparatus(es) 102 will be discussed later in further detail with reference to Fig. 2,

according to an embodiment of the disclosure.

The device(s) 104 can, for example, correspond to/be representative of at least one GNSS. In one embodiment, the device(s) 104 can be configured to determine positional location in relation to a vehicle. For example, the device(s) 104 can be configured to generate and communicate positional data (e.g., GPS data) in relation to a vehicle. Positional data can, for example, include one or both of longitude data and latitude data (e.g., longitude data and/or latitude data). The device(s) 104 can be further configured to communicate positional data to one or both of the apparatus(es) 102 and the host device(s), in accordance with an embodiment of the disclosure. In one embodiment, the device(s) 104 can be further configured to communicate positional data to the apparatus(es) 102 for further processing as will be discussed later with reference to Fig. 2.

The host device(s) (e.g., one or more computers or one or more databases) can, for example, be configured to host/carry a platform (software and/or hardware platform) configured to perform one or more processing tasks which can, for example, include one or both of learning-based processing tasks (e.g., machine-learning based processing) and prediction-based processing. In one embodiment, the host device(s) can be configured to process received positional data and generate, for example, one or more prediction signals (i.e., also referable to as prediction data). In one example, the prediction signal(s) can be communicated from the host device(s) to, for example, the apparatus(es) 102 for further processing, in accordance with an embodiment of the disclosure.

The communication network 106 can, for example, correspond to an Internet communication network, a wired-based communication network, a wireless-based communication network, or any combination thereof. Communication (i.e., between the apparatus(es) 102, the device(s) 104 and the host device(s), or any combination thereof) via the communication network 106 can be by manner of one or both of wired communication and wireless communication.

Earlier mentioned, the apparatus(es) 102 can be configured to generate and/or receive one or more input signals and process the input signal(s) in a manner so as to produce one or more output signals. The output signal(s) can, in one example, be one or both of visually perceivable and audibly perceivable (i.e., visually perceivable and/or audibly perceivable). The output signal(s) can, in another example, be communicated for further processing. The output signal(s) can, in yet another example, be visually and/or audibly perceivable, and be communicated for further processing. This will be discussed in further detail in the context of an example implementation hereinafter.

Generally, the present disclosure contemplates that the input signals can be received by the apparatus(es) 102 and processed to produce the output signal(s).

The input signals can include/be based on one or both of the aforementioned vehicle heading data and positional data, in accordance with an embodiment of the disclosure. The input signal(s) can, as an option, further include/be based on one or more prediction signal(s) in addition to the vehicle heading data and positional data (i.e., vehicle heading data, positional data and prediction signal(s)), in accordance with another embodiment of the disclosure.

As an option, in one embodiment, the input signal(s) can include/be based on vehicle heading data and/or positional data. The input signal(s) and/or the prediction signal(s) can be received by the apparatus(es) 102 and processed to produce the output signal(s). The present disclosure contemplates the possibility that, in one embodiment, the input signal(s) and the prediction signal(s) can be distinct inputs to the apparatus(es) 102 for processing.

In the example implementation, the input signal(s) can, in a first example scenario, include/be based primarily on the vehicle heading data and the positional data, in

accordance with an embodiment of the disclosure.

As mentioned earlier, vehicle heading data can relate to compass direction in which the vehicle front end (e.g., a grille) is pointed/facing. The apparatus(es) 102 can, for example, be configured to determine heading of the vehicle (i.e., vehicle heading data), in accordance with an embodiment of the disclosure.

It is contemplated that vehicle heading data can be indicative of whether path of travel direction of the vehicle is circular (i.e., circular based path of travel) or not (e.g., straight-line based path of travel). This will be discussed later in further detail with reference to Fig. 5, in the context of an example detection/determination flow diagram, in accordance with an embodiment of the disclosure.

Further earlier mentioned, the present disclosure contemplates that it is possible to perform adjustment-based processing and/or filtering-based processing in connection with the vehicle heading data based on, for example, whether the vehicle is traveling a circular direction (i.e., circular based path of travel) or not ((e.g., a non-circular based path of travel such as a straight-line based path of travel).

In the example implementation, when it is determined, based on vehicle heading data, that traveling path of the vehicle circular-based (e.g., the vehicle is being driven, by a driver and/or autonomously, in a manner such that the vehicle is moving is a circular based path of travel), the apparatus(es) 102 can be configured to generate one or more output signals indicative of vehicle coordinates. Vehicle coordinates can, for example, include/be associated with one or both of at least one latitude coordinate of the vehicle and at least one longitude coordinate of the vehicle, in accordance with an embodiment of the disclosure. Specifically, the apparatus(es) 102 can be configured to generate one or more output signal(s) indicative that the vehicle coordinates can, for example, correspond to positional data (which can, for example, include one or both of longitude data and latitude data, as mentioned earlier) received from the device(s) 104. For example, the output signal(s) can be indicative that latitude coordinate(s) of the vehicle can correspond to the aforementioned latitude data and/or longitude coordinate(s) of the vehicle can correspond to the aforementioned longitude data.

In the example implementation, when it is determined, based on vehicle heading data, that traveling path of the vehicle non-circular based (e.g., the vehicle is being driven, by a driver and/or autonomously, in a manner such that the vehicle is moving is a straight-line based path of travel), the apparatus(es) 102 can be configured to generate one or more output signals indicative of vehicle coordinates. Specifically, the apparatus(es) 102 can be configured to generate one or more output signal(s) by manner of adjustment-based processing of positional data (which can, for example, include one or both of longitude data and latitude data, as mentioned earlier) received from the device(s) 104, where appropriate (i.e., depending on vehicle heading data). Adjustment-based processing of received positional data can include applying one or more adjustment factors to the received positional data. Applying an adjustment factor can include taking into account vehicle heading data and applying a correction parameter, where appropriate. In this regard, the output signal(s) can correspond to adjusted positional data. For example, the output signal(s) can be indicative that latitude coordinate(s) of the vehicle can correspond to adjusted latitude data (i.e., adjusted based on the aforementioned adjustment-based processing) and/or longitude coordinate(s) of the vehicle can correspond to adjusted longitude data (i.e., adjusted based on the aforementioned adjustment-based processing). This will be discussed later in further detail with reference to Fig. 2.

In the example implementation, the input signal(s) can, in a second example scenario, include/be based on the vehicle heading data, the positional data and the prediction signal(s), in accordance with an embodiment of the disclosure.

The second example scenario can be largely similar to the earlier discussed first example scenario. In this regard, relevant portion(s) in connection with the first example scenario as discussed above can analogously apply in connection with the second example scenario. One distinction (as between the first and second example scenarios) is that the prediction signal(s), per the second example scenario, can facilitate prediction of possible subsequent positional data until actual positional data is received by the apparatus(es) 102 from the device(s) 104. This will be discussed later in further detail with reference to Fig. 2.

The output signal(s) can, in one embodiment, be visually perceivable. In one example, the apparatus(es) 102 can further include a display screen (not shown) which can be configured to display the vehicle coordinates. In another example, the output signal(s) can be communicated to another device (not shown) which can have a display screen configured to be capable of displaying the vehicle coordinates.

The output signal(s) can, in another embodiment, be audibly perceivable. In one example, the apparatus(es) 102 can further include an audio part (not shown) such as a speaker which can be configured to audibly output information corresponding to the vehicle coordinates. In another example, the output signal(s) can be communicated to another device (not shown) which can have an audio part configured to be capable of audibly outputting information corresponding to the zo vehicle coordinates.

The output signal(s) can, in yet another embodiment, be communicated for further processing. Examples of further processing can include one or both of the aforementioned learning-based processing and prediction-based processing. In one example, the output signal(s) can be communicated to the host device(s) for further processing (e.g., prediction-based processing). In another example, the apparatus(es) 102 can be configured to further process (e.g., by manner of prediction-based processing) the output signal(s). In yet another example, the output signal(s) can be communicated for further processing by the host device(s) and the apparatus(es) 102 (e.g., for prediction-based processing by the apparatus(es) 102 and for learning-based processing by the host device(s), or for prediction-based processing by both the apparatus(es) 102 and the host device(s)).

In yet a further embodiment, the output signal(s) can be any one of visually perceivable, audibly perceivable and communicable for further processing, or any combination thereof.

The aforementioned apparatus(es) 102 will be discussed in further detail with reference to Fig. 2 hereinafter.

Referring to Fig. 2, an apparatus 102 is shown in further detail in the context of an exemplary implementation 200, according to an embodiment of the disclosure.

In the exemplary implementation 200, the apparatus 102 can carry any one of a first module 202, a second module 204, a third module 206, or any combination thereof.

As an option, the apparatus 102 can further carry a fourth module (not shown). As a further option, the apparatus 102 can further carry a sensor.

In one embodiment, the apparatus 102 can carry a first module 202, a second module 204 and, optionally, a third module 206, a fourth module and/or a sensor. In a specific example, the apparatus 102 can carry a first module 202, a second module 204, a third module 206, a fourth module and a sensor. In another specific example, the apparatus 102 can carry a first module 202 and a second module 204.

The first module 202 can be coupled to any one of the second module 204, the third module 206, the fourth module and the sensor, or any combination thereof The second module 204 can be coupled to any one of the first module 202, the third module 206, the fourth module and the sensor, or any combination thereof The third module 206 can be coupled to any one of the first module 202, the second module 204, the fourth module and the sensor, or any combination thereof The fourth module can be coupled to any one of the first module 202, the second module 204, the third module 206 and the sensor, or any combination thereof. The sensor can be coupled to any one of the first module 202, the second module 204, the third module 206 and the fourth module, or any combination thereof. Coupling between the first module 202, the second module 204, the third module 206, the fourth module and/or the sensor can, for example, be by manner of one or both of wired coupling and wireless coupling. Each of the first module 202, the second module 204, the third module 206 and the fourth module can correspond to one or both of a hardware-based module and a software-based module, according to an embodiment of the disclosure. The sensor can, for example, be hardware based.

In one example, the first module 202 can correspond to a hardware-based receiver which can be configured to receive the input signal(s).

The second module 204 can, for example, correspond to a hardware-based processor which can be configured to perform one or more processing tasks based on the input signal(s) to produce one or more output signals.

The third module 206 can correspond to a hardware-based transmitter which can be configured to transmit the output signal(s).

The fourth module can, for example, correspond to a hardware-based prediction module which can be configured to receive further process the output signal(s) by manner of, for example, prediction-based processing to generate one or more prediction signals. The output signal(s) can, in one example, be communicated to the fourth module from the second module 204. In another example, the output signal(s) can be communicated to the fourth module from the third module 206. In yet another example, the output signal(s) can be communicated to the fourth module from both the second and third modules 204/206.

The sensor can, for example, be a hardware-based module which can be configured to sense compass direction in which the front end (e.g a grille) of the vehicle is zo pointed/facing, and generate vehicle heading data.

The present disclosure contemplates the possibility that the first and third modules 202/206 can be an integrated software-based transceiver module (e.g., an electronic part which can carry a software program/algorithm in association with receiving and transmitting functions/an electronic module programmed to perform the functions of receiving and transmitting). Moreover, the fourth module can possibly be a software-based module which can, for example, be carried by the second module 204. Furthermore, the fourth module can possibly include a combination of software aspect(s) (e.g., algorithm in association with prediction-based processing) and hardware aspect(s) (e.g., hardware transceiver for receiving the output signal(s) and communicating the prediction signal(s) and/or a processor for processing the received output signal(s)).

Earlier mentioned, the first module 202 can correspond to a hardware-based receiver which can be configured to receive the input signal(s). Additionally, the second module 204 can, for example, correspond to a hardware-based processor which can be configured to perform one or more one or more processing tasks on the received and/or generated input signal(s) to produce one or more output signals.

Furthermore, the input signal(s) can, for example, include vehicle heading data and/or positional data. Input signal(s) can, optionally, further include one or more prediction signal(s).

Positional data can, for example be communicated from the device(s) 104. The prediction signal(s) can, for example, be communicated from one or both of the fourth module and the host device(s), in accordance with an embodiment of the disclosure.

As mentioned earlier, the apparatus 102 can be configured to process the input signal(s) and generate one or more output signal(s) by manner of adjustment-based processing of positional data where appropriate (i.e., based on the vehicle heading data). Adjustment-based processing of received positional data can include applying one or more adjustment factors to the received positional data. Applying an adjustment factor can include taking into account vehicle heading data and applying a correction parameter where appropriate. The output signal(s) can correspond to adjusted positional data The foregoing discussion will now be further discussed based on the earlier discussed first and second example scenarios hereinafter.

In the first example scenario, as mentioned earlier, the input signal(s) can include/be based the vehicle heading data and the positional data. Positional data can include, for example, longitude data and/or latitude data. Positional data can be communicated from the device(s) 104.

The apparatus 102 can be configured to determine whether a vehicle is moving in a circular path of travel or not (i.e., non-circular path of travel), in accordance with an embodiment of the disclosure.

When it can be determined that the path of travel is circular (i.e., vehicle heading data being indicative of circular path of travel), the apparatus 102 can be configured to process, via the second module 204, the received positional data so that the output signal(s) can indicate that latitude coordinate(s) of the vehicle can correspond to the latitude data and/or longitude coordinate(s) of the vehicle can correspond to the longitude data For example (also referable to a first correction set for ease of reference): * Latitude coordinate = Vehicle GPS latitude received * Longitude coordinate = Vehicle GPS longitude received When it can be determined that the path of travel is non-circular, the apparatus 102 can be configured to process, via the second module 204, the received positional data by manner of adjustment-based processing where, for example, a first adjustment factor can be applied to latitude data and a second adjustment factor can be applied to the longitude data. For example (also referable to a second correction set for ease of reference): * Latitude coordinate = Last Vehicle GPS latitude received + (cosine (Heading of Last vehicle state)*0.000016541) * Longitude coordinate = Last Vehicle GPS longitude received + (cosine (Heading of Last vehicle state)* 0.00000122) Therefore, with vehicle heading data being indicative of non-circular path of travel, the apparatus 102 can be configured to process the input signals) based on adjustment-based processing to produce the output signal(s) which can correspond to adjusted positional data. Adjusted positional data can include latitude coordinate(s) of the vehicle corresponding to adjusted latitude data and longitude coordinate(s) of the vehicle corresponding to adjusted longitude data. Adjusted latitude data can be based on, for example, the last known vehicle GPS latitude (data) received and the first adjustment factor. Adjusted longitude data can be based on, for example, the last known vehicle longitude (data) received and the second adjustment factor.

The first adjustment factor can, for example, be associated with a correction parameter of "(cosine(Heading of Last vehicle state)*0.000016541" as mentioned above. That is, in one example, taking a cosine computation of the last known heading of the vehicle (i.e., last known/latest vehicle heading data) and multiplying that with a factor of "0.000016541" the first adjustment factor can be derived/determined. Adjusted latitude data can be based on an addition of the last known vehicle GPS latitude (data) received and the first adjustment factor, in accordance with an embodiment of the disclosure.

The second adjustment factor can, for example, be associated with a correction parameter of "(cosine (Heading of Last vehicle state)* 0.00000122)" as mentioned above. That is, in one example, taking a cosine computation of the last known heading of the vehicle (i.e., last known/latest vehicle heading data) and multiplying that with a factor of "0.00000122" the second adjustment factor can be derived/determined. Adjusted longitude data can be based on an addition of the last known vehicle GPS longitude (data) received and the second adjustment factor, in accordance with an embodiment of the disclosure.

The present disclosure contemplates that, in one embodiment, processing of received positional data in the manner discussed above can be carried out (i.e., continue) as long as the vehicle remains in motion. The present disclosure contemplates that, in another embodiment, processing of received positional data in the manner discussed above can be aborted as desired (e.g., by a user or a driver of the vehicle).

In the second example scenario, as mentioned earlier, the input signal(s) can include/be based the vehicle heading data, the positional data and the prediction signal(s) (i.e., also referable to as prediction data). Positional data can include, for example, longitude data and/or latitude data. Positional data can be communicated from the device(s) 104. The apparatus 102 can be configured to determine whether a vehicle is moving in a circular path of travel or not (i.e., non-circular path of travel), in accordance with an embodiment of the disclosure.

Earlier mentioned, the second example scenario can be largely similar to the earlier discussed first example scenario. In this regard, relevant portion(s) in connection with the first example scenario as discussed above can analogously apply in 10 connection with the second example scenario. For example: When it can be determined that the path of travel is circular (i.e., vehicle heading data being indicative of circular path of travel), the apparatus 102 can be configured to process, via the second module 204, the received positional data so that the output signal(s) can indicate that latitude coordinate(s) of the vehicle can correspond to the latitude data and/or longitude coordinate(s) of the vehicle can correspond to the longitude data For example (also referable to a first correction set for ease of reference): * Latitude coordinate = Vehicle GPS latitude received * Longitude coordinate = Vehicle GPS longitude received When it can be determined that the path of travel is non-circular, the apparatus 102 can be configured to process, via the second module 204, the received positional data by manner of adjustment-based processing where, for example, a first adjustment factor can be applied to latitude data and a second adjustment factor can be applied to the longitude data. For example (also referable to as a second correction set for ease of reference): * Latitude coordinate = Last Vehicle GPS latitude received + (cosine (Heading of Last vehicle state)*0.000016541) * Longitude coordinate = Last Vehicle GPS longitude received + (cosine (Heading of Last vehicle state)* 0.00000122) Therefore, with vehicle heading data being indicative of non-circular path of travel, the apparatus 102 can be configured to process the input signals) based on adjustment-based processing to produce the output signal(s) which can correspond to adjusted positional data. Adjusted positional data can include latitude coordinate(s) of the vehicle corresponding to adjusted latitude data and longitude coordinate(s) of the vehicle corresponding to adjusted longitude data. Adjusted 113 latitude data can be based on, for example, the last known vehicle GPS latitude (data) received and the first adjustment factor. Adjusted longitude data can be based on, for example, the last known vehicle longitude (data) received and the second adjustment factor.

Further mentioned earlier, one distinction (as between the first and second example scenarios) is that the prediction signal(s), per the second example scenario, can facilitate prediction of possible subsequent positional data until actual positional data is received by the apparatus(es) 102 from the device(s) 104.

In this regard, prediction data corresponding to possible subsequent positional data can be generated and communicated for further processing to generate the output signal(s). In this regard, one or more input signals corresponding to possible subsequent positional data can be processed by, for example, the second module 204 in a manner discussed earlier (i.e., taking into account vehicle heading data and performing adjustment-based processing where appropriate etc.) to generate one or more output signal(s) until actual positional data is received by the apparatus(es) 102 from the device(s) 104. Therefore, in one embodiment, the apparatus 102 can be configured to process possible subsequent positional data (i.e., not actually communicated from the device(s) 104) in the event/situation of actual positional data communicated from the device(s) 104 not being available. The apparatus 104 can be configured to process actual positional data (i.e., communicated from the device(s) 104) when available and not the prediction data, in accordance with an embodiment of the disclosure. In this regard, it is appreciable that, in one embodiment, processing of actual positional data (i.e., communicated from the device(s) 104) can be considered to be prioritized over the processing of the prediction data.

The present disclosure contemplates that generating the prediction data and processing prediction data to generate the output signal(s) in the event/situation of actual positional data communicated from the device(s) 104 not being available can possibly facilitate improved reliability, integrity and/or robustness as it is not necessary to be entirely dependent on actual positional data to be communicated from the device(s) 104 so as to have some indication of vehicle coordinate(s).

Moreover, the prediction data can serve as some form of backup/secondary input in the event/situation of actual positional data from the device(s) 104 not being available (e.g., due to poor communication network connectivity). Furthermore, the prediction data can possibly be usable as some form of reference (e.g., for comparison, by manner of, for example, comparison-based processing which can be performed by, for example, one or both of the second module 204 and the fourth module, in accordance with an embodiment of the disclosure) to provide a certain degree of indication as to reliability of actual positional data (e.g., whether there are any errors such as data corruption in the actual positional data) communicated from the device(s) 104.

Analogous to the first example scenario, for the second example scenario, in one embodiment, processing of received positional data in the manner discussed above can be carried out (i.e., continue) as long as the vehicle remains in motion. In another embodiment, processing of received positional data in the manner discussed above can be aborted as desired (e.g., by a user or a driver of the vehicle).

For the first and second example scenarios, it is contemplated that the aforementioned adjustment-based processing can be based on the following considerations: 1. Analysis of GPS Data for multiple vehicle recordings and compare to ground truth data.

2. The logic behind adjustment-based processing: a. The less-accurate Vehicle GPS, which is to be corrected is taken as a parameter to work on.

b. The previous heading angle of the vehicle can be considered in order to determine the next location.

c. The cosine value of the angle is utilized because cosine of the angle will point towards the base direction where the vehicle is supposed to move d. The error correction values multiplied with the cosine value have been estimated using Non-Linear Polynomial Fit and validated against a satisfactory number of data.

In view of the foregoing, it is appreciable that the present disclosure can generally relate to an apparatus 102 suitable for improving accuracy of positional data in relation to, for example, a vehicle (not shown).

Generally, the apparatus 102 can be suitable for use in association with a vehicle, in accordance with an embodiment of the disclosure. The apparatus 102 can, in one embodiment, include a first module 202 and a second module 204. The first and second modules 202/204 can be coupled.

The first module 202 can be configured to receive at least one input signal and the second module can be configured the input signal(s) to produce at least one output signal.

The input signal(s) can include vehicle data and positional data.

Vehicle data can be communicated from at least one sensor (e.g., carried by the vehicle and/or the apparatus 102). The sensor(s) can be coupled to the first module 202. Moreover, vehicle data can be indicative of whether path of travel of the vehicle is either circular or non-circular (e.g., a straight-lined path of travel).

Positional data can be communicated from at least one device 104 coupled to the apparatus 102. Furthermore, the positional data can, for example, include longitude data and latitude data in association with the vehicle, in accordance with an embodiment of the disclosure. Additionally, in one example, the positional data can correspond to global positioning system (GPS) based vehicle data, in accordance with an embodiment of the disclosure.

In one embodiment, the apparatus 102 can, for example, further include a fourth module which can correspond to a prediction module. The prediction module can, for example, be configured to receive and further process the output signal(s) to generate at least one prediction signal. The output signal(s) can, for example, be processed by manner of prediction-based processing to generate at least one prediction signal which can be communicated to the first module 202. The first module 202 can, in turn, communicate (i.e., also referrable to as forward communication) the prediction signal(s) to the second module 204 for further processing. In this regard, it is appreciable that the second module 204 can, for example, be configured to generate the output signal(s) based on the input signal(s) and the one prediction signal(s), in accordance with an embodiment of the disclosure.

As mentioned earlier, it is appreciable that the present disclosure generally contemplates that in the above manner, accuracy of positional data communicated from, for example, a GNSS can possibly be improved. By taking into account vehicle heading data and distinguishing between circular and non-circular path of travel for the purpose of generating the output signal(s) in the above discussed manner, accuracy of positional data communicated from, for example, a GNSS can be improved. Thus it is possible that more accurate information concerning vehicle coordinates can be facilitated. Appreciably, the present disclosure contemplates using (comparatively) less-accurate positional data (as communicated from, for example, a GNSS) in conjunction with the latest (e.g., updated or real-time) vehicle heading data to possibly mitigate one or more errors associated with positional data so as to improve accuracy of received positional data.

The above-described advantageous aspect(s) of the apparatus 102 of the present disclosure can also apply analogously (all) the aspect(s) of a below described processing method 300 of the present disclosure. Likewise, all below described advantageous aspect(s) of the processing method 300 of the disclosure can also apply analogously (all) the aspect(s) of above described apparatus 102 of the disclosure. It is to be appreciated that these remarks apply analogously to the earlier discussed system 100 of the present disclosure.

Referring to Fig. 3, a processing method 300 in association with the system 100 is shown, according to an embodiment of the disclosure.

The processing method 300 can be suitable for improving accuracy of positional data in relation to, for example, a vehicle (not shown). The processing method 300 can include any one of a receiving step 302, a processing step 304 and an output generating step 306, or any combination thereof, in accordance with an embodiment of the disclosure.

In one embodiment, the processing method can include a receiving step 302, a processing step 304 and an output step 306. In another embodiment, the processing method can include a receiving step 302 and a processing step 304.

With regard to the receiving step 302, one or both of the input signal(s) and the prediction signal(s) can be received by the apparatus(es) 102. In one embodiment, the input signal(s) can further include/be further based on the prediction signal(s). In another embodiment, the input signal(s) and the prediction signal(s) can be considered to be distinct inputs received by, for example, the apparatus(es) 102 for processing.

With regard to the processing step 304, the input signal(s) and/or the prediction signal(s) can be processed by the apparatus(es) 102 in a manner so as to generate the output signal(s).

With regard to the output step 306, the output signal(s) can be communicated from the apparatus(es) 102. As an option, as mentioned earlier, the output signal(s) can be received and processed by, for example, the fourth module (e.g a prediction module) to generate one or more prediction signals.

In this regard, the present disclosure generally contemplates, in one embodiment, a processing method 300 which can be suitable for improving accuracy of positional data in relation to, for example, a vehicle (not shown).

Generally, the processing method 300 can be in association with a vehicle. The processing method 300 can include a receiving step 302 and a processing step 304, in accordance with an embodiment of the disclosure.

The receiving step 302 can include receiving at least one input signal. In one embodiment, the input signal(s) can be received by, for example, the first module 202 of the earlier mentioned apparatus 102. The input signal(s) can include vehicle data indicative of path of travel of the vehicle and positional data. The vehicle data can, for example, be communicated from at least one sensor (e.g., which can be carried by one or both of the vehicle and the apparatus 102), in accordance with an embodiment of the disclosure. Moreover, the positional data can, for example, be communicated from the device 104.

The processing step 304 can include processing the received input signal(s) to generate at least one output signal. The input signal(s) can be processed by the 20 second module 204 of the earlier mentioned apparatus 102.

In one embodiment, the processing method 300 can further include receiving at least one prediction signal for further processing to generate at least one output signal.

The prediction signal(s) can, for example, be generated by the fourth module (e.g., the prediction module) of the earlier mentioned apparatus 102. In one example, the fourth module can, for example, be configured to receive and further process the output signal(s) to generate at least one prediction signal. The output signal(s) can, for example, be processed by manner of prediction-based processing to generate at least one prediction signal, in accordance with an embodiment of the disclosure.

The present disclosure further contemplates a computer program (not shown) which can include instructions which, when the program is executed by a computer (not shown), cause the computer to carry out any one of, or any combination of, the receiving step 302, the processing step 304 and the output generating step 306, as discussed with reference to the processing method 300.

The present disclosure yet further contemplates a computer readable storage medium (not shown) having data stored therein representing software executable by a computer (not shown), the software including instructions, when executed by the computer, to carry out any one of, or any combination of, the receiving step 302, the processing step 304 and the output generating step 306, as discussed with reference to the processing method 300.

Moreover, by manner of the above discussed processing (e.g., manner of processing based on a distinction as between whether path of travel is circular or non-circular), the present disclosure contemplates that complicated computations (i.e., processing) which may require significant processing resources can possibly be unnecessary.

Specifically, in the above manner, accuracy of received positional data can possibly be facilitated in a more efficient manner (i.e., possibly a more efficient manner of processing for possible improvement in accuracy of received positional data).

Fig. 4a and Fig. 4b show, respectively, a first example flow diagram 400a and a second flow diagram 400b in association with the processing method 300, according to an embodiment of the disclosure. Fig. 4c shows a first example case 400c in association with the first example flow diagram 400a, in accordance with an embodiment of the disclosure. Fig. 4d shows a second example case 400d in association with the second example flow diagram 400b, in accordance with an embodiment of the disclosure.

Referring to Fig. 4a, a first example flow diagram 400a in association with the processing method 300 is shown, in accordance with an embodiment of the disclosure.

The first example flow diagram 400a can include receiving the aforementioned input signal(s) 402 and checking whether a vehicle is moving in a circular path or not 404. As mentioned earlier, the input signal(s) can, for example, be received by the first module 202 in accordance with an embodiment of the disclosure.

If the vehicle is traveling in a circular path 404a, adjustment can be carried out/performed based on the aforementioned first correction set 406. If the vehicle is traveling in a non-circular path 404b, adjustment/correction can be performed based on the aforementioned second correction set 408. Subsequently, the aforementioned output signal(s) can be communicated 410.

In one example, the first correction set can, as mentioned earlier, be based on: * Latitude coordinate = Vehicle GPS latitude received * Longitude coordinate = Vehicle GPS longitude received In one example, the second correction set can, as mentioned earlier, be based on: * Latitude coordinate = Last Vehicle GPS latitude received + (cosine (Heading of Last vehicle state)*0.000016541) * Longitude coordinate = Last Vehicle GPS longitude received + (cosine (Heading of Last vehicle state)* 0.00000122) Moreover, the input signal(s) can, for example, include vehicle GPS data received at a regular interval and vehicle heading data received at the latest processing frame, in accordance with an embodiment of the disclosure.

Furthermore, the output signal(s) can, for example, include/correspond to corrected GPS data, in accordance with an embodiment of the disclosure.

Additionally, as an option, the output signal(s) can be communicated as, for example, 25 a form of feedback for further processing, in accordance with an embodiment of the disclosure. In this regard, the input signal(s) can further include, for example, corrected GPS data, in accordance with an embodiment of the disclosure.

Referring to Fig. 4b, a second example flow diagram 400b in association with the 30 processing method 300 is shown, in accordance with an embodiment of the disclosure.

The second example flow diagram 400b can be largely similar to the earlier discussed first example flow diagram 400a. In this regard, relevant portion(s) in connection with the first example flow diagram 400a as discussed above can analogously apply in connection with the second example flow diagram 400b. For

example:

The second example flow diagram 400b can include receiving the aforementioned input signal(s) 402 and checking whether a vehicle is moving in a circular path or not 404. If the vehicle is traveling in a circular path, adjustment can be carried out/performed based on the aforementioned first correction set 406. If the vehicle is traveling in a non-circular path, adjustment/correction can be performed based on the aforementioned second correction set 408. Subsequently, the aforementioned output signal(s) can be communicated 410.

One distinction (as between the first and second example flow diagrams 400a/400b) is that the second example flow diagram 400b can, for example, further include prediction-based processing 412, in accordance with an embodiment of the disclosure. For example, the corrected GPS data can be further processed by manner of prediction-based processing to generate prediction data. It is contemplated that by doing so, prediction of possible subsequent positional data can be facilitated until, for example, actual positional data is received (e.g., by the apparatus(es) 102 from the device(s) 104). In this regard, prediction data corresponding to possible subsequent positional data (e.g., possible subsequent vehicle GPS data) can be generated and communicated for further processing. In this regard, the input signal(s) can further include, for example, one or both of corrected GPS data and prediction data, in accordance with an embodiment of the disclosure.

Referring to Fig. 4c a first example case 400c in association with the first example flow diagram 400a is shown, in accordance with an embodiment of the disclosure. In one embodiment, the first example flow diagram 400a can, for example, be representative of an algorithm 450 (e.g., referable to as a first algorithm 450) which can be associated with a plurality of processing frames.

As shown, in the first example case 400c, label 450a indicates receipt of a first set of vehicle GPS data and labels 450b to 450j can indicate subsequent (i.e., subsequent to the receipt of the first set of vehicle GPS data) receipt of vehicle GPS data (e.g., vehicle GPS data communicated from the device(s) 104 and received by the apparatus(es) 102). For example, label 450b can indicate receipt of a second set of vehicle GPS data (i.e., subsequent to the first set of vehicle GPS data as represented by label 450a) and label 450j can indicate receipt of a tenth set of vehicle data (i.e., subsequent to the ninth set of vehicle GPS data as represented by label 450i). The plurality of sets of vehicle GPS data (i.e., as represented by labels 450a to 450j) can, for example, be received during a plurality of processing frames associated with the aforementioned first example flow diagram 400a. For example, the first set of vehicle GPS data 450a can be received during a processing frame (e.g., a first processing frame), the second set of vehicle GPS data 450b can be received during another processing frame (e.g., a second processing frame), the third set of vehicle GPS data 450c can be received during yet another processing frame (e.g., a third processing frame), and so on and so forth. Alternatively, in accordance with an embodiment of the disclosure, a plurality of sets of vehicle GPS data (e.g., the first and second sets of vehicle GPS data 450a/450b) can, for example, be received during a processing frame (e.g., during the first processing frame). The present disclosure contemplates that vehicle GPS data can, for example, be received at every processing frame and processing, in connection with the first algorithm 450, can be performed at every processing frame. In one embodiment, the first algorithm 450 can, for example, be associated with one or more portions/parts of the earlier discussed processing method 300.

Referring to Fig. 4d a second example case 400d in association with the second example flow diagram 400b is shown, in accordance with an embodiment of the disclosure.

In the second example case 400d, as shown, in association with the first example flow diagram 400a is shown, in accordance with an embodiment of the disclosure. In one embodiment, the second example flow diagram 400a can, for example, be representative of another algorithm 460 (e.g., referable to as a second algorithm 460) which can be associated with a plurality of processing frames.

As shown, in the second example case 400d, label 460a indicates receipt of a first set of vehicle GPS data and labels 460b and 460c can indicate subsequent (i.e., subsequent to the receipt of the first set of vehicle GPS data) receipt of vehicle GPS data (e.g., vehicle GPS data communicated from the device(s) 104 and received by the apparatus(es) 102). For example, label 460b can indicate receipt of a second set of vehicle GPS data (i.e., subsequent to the first set of vehicle GPS data as represented by label 460a) and label 460c can indicate receipt of a third set of vehicle data (i.e., subsequent to the second set of vehicle GPS data as represented by label 460b). The plurality of sets of vehicle GPS data (i.e., as represented by labels 460a to 460c) can, for example, be received at regular time-based intervals (e.g., intervals of 1 second). The present disclosure contemplates that, in one embodiment, vehicle GPS data received (i.e., actual GPS data communicated from, for example, the device(s) 104) can, for example, be received (e.g., by the apparatus(es) 102) at a time-based interval of 1 second and processing, in connection with the second algorithm 460, can be performed in association with only the received vehicle GPS data. Between the time-based intervals, prediction data can be generated and processed (as discussed earlier) during one or more processing frames (e.g., during every processing frame at, for example, 60 milliseconds each), in accordance with an embodiment of the disclosure. Appreciably, prediction data can be used only if actual GPS data is not available. For example, when actual GPS data is received at the aforementioned time-based interval of 1 second, processing can only be in association with actual GPS data and not prediction data (i.e., actual GPS data can be considered to be prioritized over the prediction data). Alternatively, in one embodiment, the present disclosure contemplates the possibility that processing can be based on the combination of actual GPS data received and prediction data. Yet alternatively, in one embodiment, the present disclosure contemplates the possibility that prediction data can be prioritized over actual GPS data, even if received, for processing. In one embodiment, the second algorithm 460 can, for example, be associated with one or more portions/parts of the earlier discussed processing method 300.

Fig. 5 shows an example detection/determination flow diagram 500 concerning path of travel of a vehicle, in association with the earlier discussed first and second example flow diagrams 400a/400b, in accordance with an embodiment of the

disclosure.

The example detection/determination flow diagram 500 can begin detecting/determining, if any, difference between previous and current vehicle heading 502 (i.e., previous vehicle heading data can be compared with current vehicle heading data to determine/detect whether or not there is a difference). If a difference can be detected/determined, it can next be determined if the difference is above and/or equal to a predetermined threshold value for a number of consecutive processing frames (e.g., 10 consecutive processing frames) 504. If it is determined/detected that the difference is not above and/or equal to a predetermined threshold value for a number of consecutive processing frames, it can be determined that path of travel is non-circular 506. Conversely, if it is determined/detected that the difference is indeed above and/or equal to a predetermined threshold value for a number of consecutive processing frames, it can be preliminarily determined that path of travel is circular 508.

Subsequent to a preliminary determination that path of travel is circular, a confirmation detection/determination can be performed. For example, for confirmation, it can be determined/detected whether the difference is less than the predetermined threshold for a number of consecutive processing frames (e.g., 3 consecutive processing frames) 510. If it is determined/detected that the difference is not less than the predetermined threshold for a number of consecutive processing frames, the path of travel can be confirmed to be circular 510a. Otherwise, if it can indeed be determined/detected that the difference is less than the predetermined threshold for a number of consecutive processing frames, the path of travel can be determined to be non-circular 510b. Thereafter, the example detection/determination flow diagram 500 can repeat (e.g., so long as the vehicle remains in motion) from the beginning (i.e., detecting/determining, if any, difference between previous and current vehicle heading 502).

It should be appreciated that the embodiments described above can be combined in any manner as appropriate (e.g., one or more embodiments as discussed in the "Detailed Description" section can be combined with one or more embodiments as described in the "Summary of the Invention" section).

It should be further appreciated by the person skilled in the art that variations and combinations of embodiments described above, not being alternatives or substitutes, may be combined to form yet further embodiments.

In one example, as mentioned earlier, the system 100 can be suitable for improving accuracy of positional data in relation to, for example, a vehicle. The present disclosure contemplates that the vehicle can be coupled to one or more part(s)/portion(s) of the system 100. For example, the vehicle can be coupled to any one of the apparatus(es) 102, the device(s) 104, the communication network 106 and the host device(s), or any combination thereof. In a more specific example, the vehicle can be coupled to one or both of the apparatus(es) 102 and the device(s) by manner of one or both of wired coupling and wireless coupling. In yet a more specific example, the apparatus(es) 102 can either be carried by the vehicle (e.g., wired coupling-based installation) or carried into the vehicle by a user (e.g., the vehicle and the apparatus(es) can be configured to signal communicate with each other by manner of wired coupling and/or wireless coupling).

In another example, as mentioned earlier, the system 100 can be suitable for improving accuracy of positional data in relation to, for example, a vehicle. The present disclosure contemplates that the earlier mentioned sensor can be omitted from the apparatus(es) 102 and carried by, for example, the vehicle. Vehicle heading data can, for example, be communicated from the sensor to the apparatus(es) 102 by manner of one or both of wired coupling and wireless coupling.

Moreover, vehicle heading data can, for example, be communicated from the sensor to one or both of the device(s) 104 and the host device(s).

In yet another example, as mentioned earlier, the prediction signal(s) can, for example, be communicated from one or both of the fourth module and the host device(s) (i.e., the fourth module and/or the host device(s)), in accordance with an embodiment of the disclosure. It is appreciable that the present disclosure contemplates that the fourth module can possibly be omitted from the apparatus(es) 102. In one example, in one embodiment, the prediction signal(s) can be communicated from the host device(s) and the apparatus(es) 102 need not include the fourth module. In another example, in one embodiment, the fourth module can possibly be carried outside of (e.g., carried by the vehicle) the apparatus(es) 102 and the apparatus(es) 102 need not include the fourth module. In yet another example, one or more portions (e.g., software aspect) of the fourth module can be carried by the apparatus(es) 102 (e.g., carried by the second module 204) and another one or more portions (e.g., hardware aspect) of the fourth module can be carried by the host device(s) and/or the vehicle.

In yet another further example, as mentioned earlier, in one embodiment, processing of actual positional data (i.e., communicated from the device(s) 104) can be considered to be prioritized over the processing of the prediction data. The present disclosure further contemplates that it may be possible for processing of a combination of the actual positional data and the prediction data (i.e., together) to generate the output signal(s), in accordance with an embodiment of the disclosure.

In yet an additional further example, it is appreciable that the foregoing discussion can be helpful for/applicable for correction/adjustment can be in connection with any type of moving objects (e.g., ships, airplanes etc.). The earlier discussed adjustment factor(s) (e.g., the earlier discussed first adjustment factor and/or second adjustment factor) may have to be varied depending on, for example, size of the object or other surrounding factors (e.g., for objects other than vehicles).

In yet another additional further example, one or both of the prediction signal(s) and the output signal(s) can be communicated to, for example, the host device(s) for learning-based processing (e.g., machine learning-based processing).

In the foregoing manner, various embodiments of the disclosure are described for addressing at least one of the foregoing disadvantages. Such embodiments are intended to be encompassed by the following claims, and are not to be limited to specific forms or arrangements of parts so described and it will be apparent to one skilled in the art in view of this disclosure that numerous changes and/or modification can be made, which are also intended to be encompassed by the following claims.

Claims

Claim(s) 1. An apparatus (102) suitable for use in association with a vehicle, the apparatus (102) comprising: a first module (202) configurable to: receive at least one input signal, the at least one input signal comprising: vehicle data communicable from at least one sensor coupled to the first module (202), vehicle data being indicative of whether path of travel of the vehicle is one of circular and non-circular; and positional data communicable from at least one device coupled to the apparatus (102), a second module (204) coupled to the first module (202), the second module (204) configurable to process the at least one input signal to produce at least one output signal, wherein based on the vehicle data, when path of travel of the vehicle is determined to be circular, the input signal is processable in a manner such that the output signal is indicative that vehicle coordinates associated with the vehicle correspond to the positional data, and wherein based on the vehicle data, when path of travel of the vehicle is determined to be non-circular, the input signal is processable by manner of adjustment-based processing to produce at least one output signal corresponding to adjusted positional data.
2. The apparatus (102) according to claim 1, further comprising a fourth module corresponding to a prediction module configurable to receive and further process the output signal to generate at least one prediction signal.
3. The apparatus (102) according to any of the preceding claims, the output signal being processable by manner of prediction-based processing to generate at least one prediction signal communicable to the first module for forward communication to the second module for further processing.
4. The apparatus (102) according to any of the preceding claims, the second module being configurable to generate output signal being based on the input signal and at least one prediction signal.
5. The apparatus (102) according to any of the preceding claims, the positional data corresponding to global positioning system (GPS) based vehicle data, wherein the positional data comprise longitude data and latitude data in association with the vehicle.
6. The apparatus (102) according to any of the preceding claims, wherein adjustment-based processing is by manner of processing the input signal based on at least one adjustment factor comprising at least one correction parameter.
7. The apparatus (102) according to any of the preceding claims, wherein adjustment-based processing is by manner of processing the input signal based on at least a first adjustment factor comprising at least one correction parameter and a second adjustment factor comprising at least one correction parameter, and wherein the first adjustment factor and the second adjustment factor are different.
8. The apparatus (102) according to any of the preceding claims, wherein adjustment-based processing is by manner of processing latitude data based on a first adjustment factor and processing longitude data based on a second adjustment factor.
9. A processing method (300) in association with a vehicle, the processing method (300) comprising: a receiving step (302) comprising receiving, by a first module (202) of an apparatus (102) of any of the preceding claims, at least one input signal comprising: vehicle data indicative of path of travel of the vehicle, and positional data; and a processing step (304) comprising processing, by a second module (204) of an apparatus (102) of any of the preceding claims, the received at least one input signal to generate at least one output signal, wherein based on the vehicle data, when path of travel of the vehicle is determined to be circular, the input signal is processable in a manner such that the output signal is indicative that vehicle coordinates associated with the vehicle correspond to the positional data, and wherein based on the vehicle data, when path of travel of the vehicle is determined to be non-circular, the input signal is processable by manner of adjustment-based processing to produce at least one output signal corresponding to adjusted positional data.
10. The processing method (300) as in claim 9, further comprising: receiving at least one prediction signal for further processing to generate at least one output signal.
11. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the receiving step (302) and the processing step (304) according to the processing method (300) of any of zo claims 9 and 10.
12. A computer readable storage medium having data stored therein representing software executable by a computer, the software including instructions, when executed by the computer, to carry out the receiving step (302) and the processing step (304) according to the processing method (300) of any of claims 9 and 10.