GB2536718A

GB2536718A - Connectivity

Info

Publication number: GB2536718A
Application number: GB1505316.8A
Authority: GB
Inventors: Glaister Alan
Original assignee: Denso Corp
Current assignee: Denso Corp
Priority date: 2015-03-27
Filing date: 2015-03-27
Publication date: 2016-09-28
Also published as: GB201505316D0

Abstract

Managing the power usage of an in-vehicle data connectivity device comprises storing mapping data that links known locations to observed wireless data signal strength and using the mapping data and a prediction of an expected route to predict when the vehicle will enter into areas of high or low wireless data signal strength. The prediction is used to choose when and/or how to make data communications, e.g. by mobile telephone network. The position of the vehicle may be determined using a satellite navigation system and used to predict the expected route of the vehicle, which may be based on historical journeys or guidance instructions to a selected destination. Current signal strength mapping data may be recorded to update previous map data from an external source. A predicted rate of change of signal strength may be determined based on the map data, predicted route and also vehicle speed.

Description

CONNECTIVITY

BACKGROUND

The present disclosure relates to connectivity, and in particular but not exclusively to approaches for optimising vehicle connectivity.

Connectivity into the vehicle is increasing with demand from users for connected services. Data connectivity to and from vehicles can be provided using a network access device to access a wireless data service. Such a wireless data service may be a data transmission mode of a cellular telephone network, such as a 2G, 2.5G, 4G or 5G data mode of the network. Where a network access device of vehicle and/or within a vehicle provides for data connectivity, data rates for a wireless data service being accessed can vary significantly, especially when the receiving unit is travelling at speed. Factors influencing the variation in achievable data rates can include slow and fast fade. Also, in areas where signal strength for the wireless data service is weak, the network access device must use more power in an attempt to obtain a stable connection with a fixed infrastructure station of the wireless data service (such as a cell tower or base station of a cellular telephone network). This will increase the power draw on a vehicle powering the network access device.

An increase in the electrical power draw on a vehicle runs contrary to reducing electrical consumption on vehicles. For vehicles based on an internal combustion engine power plant, a reduction in electrical power consumption can reduce alternator load and drag. For so-called hybrid, plug-in hybrid and electric vehicles where battery power is used as a primary or auxiliary power source for propulsion, a reduction in electrical power consumption can maintain or increase the maximum performance and/or range of the vehicle.

Some different approaches for mobile data are described in U52011/166741A1, JPH10- 19591A; JP2006108921; JP2008203040A; W02005/094110, EP1732341A1, and JP2003035544A.

SUMMARY

Particular aspects and embodiments are set out in the accompanying claims.

Viewed from a first perspective, the present teachings can provide apparatus for managing power usage of an in-vehicle data connectivity device, the apparatus comprising: storage configured to hold mapping data that links known locations to observed wireless data signal strength; and a controller configured to use the mapping data and a prediction of an expected route to predict when the vehicle will enter into areas of high or low wireless data signal strength and to use the prediction to choose when to make and pause data communications. Thereby, data transmission can be scheduled to avoid data transmission at times or locations when low signal strength would cause high transmission power consumption. Viewed from a second perspective, the present teachings can provide a method for managing power usage of an in-vehicle data connectivity device, the method comprising: using mapping data that links known locations to observed wireless data signal strength and a prediction of an expected route to predict when the vehicle will enter into areas of high or low wireless data signal strength; and using the prediction to choose when to make and pause data communications. Thereby, data transmission can be controlled to optimise data transmission power usage by avoiding times or locations when low signal strength would cause high transmission power consumption.

Further feature combinations provided by the present teachings will be understood from the following detailed description and the accompanying figures.

BRIEF DECSRIPTION OF THE FIGURES

The present teachings will now be described by way of example only and with reference to the following drawings in which like numerals reflect like elements: Figure 1 is an example of a vehicle having a wireless connectivity implementation; Figure 2 is an example of a geography; Figure 3 is a schematic illustration of logical blocks in a data handling system for a vehicle; Figure 4 is an example of a route portion through a geography; Figure 5 is a schematic illustration of operation states for a data handling system for a vehicle; and Figure 6 is a schematic illustration of operation states for a data handling system for a vehicle.

VVhile the present teachings are susceptible to various modifications and alternative forms, specific embodiments are shown by way of example in the drawings and are herein described in detail. It should be understood however that drawings and detailed description attached hereto are not intended to limit the scope of protection to the particular form disclosed but rather the scope is to cover all modifications, equivalents and alternatives falling within the scope of the appended claims.

DETAILED DESCRIPTION

The presently described approaches operate in the context of a movable vehicle such as a car, van, truck, lorry or motorcycle provisioned with a network access device that can provide data connectivity between the movable vehicle and a wirelessly-accessible data service. The approaches of the examples described below provide for implementation of a system which can operate to manage data connectivity activity in a manner that is predicted to provide for efficient power usage by the network access device.

Figure 1 illustrates a connectivity environment in which a vehicle 1 is configured to wirelessly communicate with a data provision service. As shown in Figure 1, the vehicle 1 has an antenna 3 connected to a network access device 5, which in turn is connected to some form of user interaction device 7. Thereby wireless signals received at the antenna 3 can be processed by the network access device 5 to provide received data that can then be used to cause some form of visual and/or audio content to be presented to a user via the user interaction device 7. The user interaction device 7 may include one or more of a display screen, a visual display indicator and a loud speaker. The user interaction device 7, the network access device 5 and/or some other device connected therebetween may provide for processing of the received data before presentation to a user. Likewise, a user input received at the user interaction device 7 may be encoded for transmission by the network access device 5 and then transmitted using the antenna 3.

Communication from the antenna 3 is with one or more wireless infrastructure antennas 11, as indicated by signals 9. The wireless infrastructure antenna 11 provides an interface point for the wireless data transmissions to and from the vehicle 1 to an existing data connectivity infrastructure.

In the present examples, it will be described that the wireless data transfer uses the data transfer capabilities of a mobile (cellular) telephone network, such as a 2g, 2.5G, 3G, 4G or 5G mobile telephone network. In this context, the wireless infrastructure antenna 11 would be a mobile telephone network antenna and the network access device 5 would be a mobile telephone network access device. It will be appreciated that other wireless data infrastructures could be used, such as long-range W-Fi or WMAX.

Referring now to Figure 2, this illustrates a geographic area through which a vehicle may travel. The geographic area includes a number of wireless infrastructure antennas 11 and one or more roads 13 passing through the geographic region. The geographic region also includes geographic features such as hills 15 and forests 17, as well as a settlement 19. As will be appreciated, when a vehicle passes through the geographic region (typically using the one or more roads 13), the mobile telephone signal strength provided by the wireless infrastructure antennas 11 will vary based upon factors such as proximity of the vehicle to one or more of the wireless infrastructure antennas 11 and signal degradation caused by geographic features such as the hills 15, forest 17 and buildings within the settlement 19.

As a result of the different mobile telephone signal strengths experienced by the vehicle as it travels through the geographic area, the network access device of the vehicle will be expected to have varying power draw requirements. In particular, where the mobile network signal strength is good, the power draw requirements of the network access device will be relatively lower as the network access device is able to maintain a reliable connection to the mobile telephone network using low transmit signal strength and/or with low received signal amplification. On the other hand, where the mobile network signal strength is poor, the power draw requirements of the network access device will be relatively higher as the network access device need to use high transmit signal strength and/or high received signal amplification to maintain a reliable connection to the mobile telephone network that provides a useful data bandwidth. As will be appreciated, different wireless transmission technologies present different power draw profiles, but it will be appreciated that a technology that can react to poor signal coverage by increasing transmit power and/or boosting received signal amplification will thereby increase its own power draw. For example, in the presently discussed context of mobile (cellular) telephone network environment, it is understood that as between 3G and 2G data transfer capabilities higher power draw is experienced for 3G operation than for 2G operation where the network coverage is patchy or fluctuating. This high draw for patchy or fluctuating coverage can result in rapid depletion of battery power reserves.

Figure 3 illustrates an example system that can be operated to alleviate high power draw situations that may occur when travelling through a region in which the wireless service coverage is known to be patchy, with areas of good coverage and areas of poor coverage.

The example system of the present examples relies upon mapping of previously measured signal reception conditions and upon route prediction to control when connected functionality elements of the vehicle 1 should attempt data communications and when to pause in order to avoid unnecessary power increases cause by attempts to gain a stable network connection. The mapping of previously measured routes may rely upon mapping and learning signal reception conditions on previous journeys and/or using reception maps collected by external providers. The route prediction may rely upon route prediction that is based upon recorded previous driving routes and/or upon routing instructions currently being presented to a driver of the vehicle by a satellite navigation system.

In some examples, the system of the present examples can also take into account signal strength changes that may be caused by slow and/or fast fade. Slow and fast fade describe a rate of signal strength change over distance. Fast fade is considered to occur in situations where large differences of signal strength occur over a small distance. On the other hand, slow fade is considered to occur in situations where small changes of signal strength over a large distance. As will therefore be appreciated, the speed of travel of a vehicle may impact the degree to which both slow and fast fade may influence the signal strength.

Thus the present teachings can be applied to controlling data transmission on the basis of predicted routing and mapped signal strength for a number of different scenarios. Various factors can be taken into account, including the nature of the vehicle (as a slow lorry may be limited to its maximum speed, for example 80kph/50mph, and some vehicles such as emergency service vehicles may be expected to travel at speed exceeding the usual maximum speed limits (which in Europe tend to range from 110kph/70mph to 140kph/90mph and in other regions or countries may be higher or lower). Another factor that can be taken into account is the previous driving history of the vehicle, for example if the vehicle is usually driven at the speed limit in most circumstances, then such a vehicle may be predicted to travel along a predicted route faster than a vehicle that is usually driven somewhat below the speed limit. A further factor that may be taken into account is present weather conditions (which may be obtained for example from radio data transmissions or from weather data retrieved over the mobile telephone network, as heavy snow conditions may be expected to cause all traffic to move somewhat slower relative to the speeds that would be expected in clear dry weather. In some arrangements, the mapping system may additionally or alternatively provide for active management of buffering for streaming so as to reduce overall memory requirements and/or increase memory usage efficiency, by controlling data transfer such as to minimise buffering times at start and interruption of streaming due to poor signal conditions.

The example system uses a navigation system receiver such as a received 21 for a global navigation satellite system (GNSS) to provide position information relating to the current position of the vehicle. Examples of global navigation satellite system include the US-built and controlled NAVSTAR GPS and the Russian-built and controlled GLONASS. Other satellite navigation systems that provide some coverage to limited geographical areas or are in development stages include the Chinese BeiDou system, the EU's Galileo system, the French DORIS system, and the Indian IRNSS. As an alternative to a satellite navigation system, some other form of radio positioning system such as a hyperbolic radio navigation system could be used, examples of which include the LORAN and LORAN-C systems.

In the system of the present example, the GNSS receiver 21 provides position information to a routing predictor 23. The routing predictor 23 operates to predict a route that the vehicle 1 is expected to follow based upon its present position. The routing predictor may take into account the route so far, for example in the sense of a route already travelled as identified by a history of position indications since the last engine start time for example. The routing predictor may take into account a route presently being presented to a drive of the vehicle in a satellite navigation route guidance mode.

The current position and any route-so-far information and guidance route information can be compared to known patterns of routes previously recorded for the vehicle. From this comparison, the route predictor can make a prediction as to the route that is considered most likely to be followed by the vehicle. Thus, for example if the vehicle is regularly used to make the same commute journey, the routing predictor may recognise the route so far as that regular commute journey and accordingly arrive at a prediction that the regular commute journey is the route currently being followed.

The predicted route can be updated on an ongoing basis, based upon changes to the current position that cause deviation from the currently predicted route. For example, while the vehicle may be regularly used for a given commute journey, it may also be used less often to travel to an alternative location but which journey to the alternative location shares an initial route portion with the regular commute journey. Thus, as the regular commute journey is the most frequently used when the vehicle is detected to be following the shared initial route portion, the predictor predicts the regular commute journey to be the most likely journey and accordingly arrives at this route as the predicted route. However, when the position information from the GNSS receiver 21 deviates from the regular commute journey but correspond to the route to the alternative location, the predicted route can be updated to correspond to the known route to that alternative location. Many such recorded routes and route usage frequencies can be stored and used to arrive at a predicted route. Also, previously followed routes may be considered both in the previously recorded direction of travel and in a reverse direction of travel.

This process may also take into account a time of the present journey and of those previously recorded routes. Thus the routing predictor 23, as well as relating the current position, and optionally the route so far, to the previously used routes, can take into account a time factor such as time of day and/or a day of the week in comparing the current route to recorded previous routes in order to arrive at a predicted route. Referring again to the above example of a regular commute and a less frequent partially overlapping journey to an alternative location, it may be that although the regular commute usually occurs most frequently on weekdays or between 6am and 10am, the journey to the alternative location may be more common on weekends or between 11am and 4pm. Thus by comparing the current time factor to the time factor(s) associated with the recorded previous journeys, the routing predictor 23 may further increase the accuracy of the routing predictions made.

In the situation where the routing predictor relies upon a route presently being presented to a drive of the vehicle 1 by a satellite navigation route guidance mode, the routing predictor 23 may simply use the route as indicated in the guidance mode as the route prediction.

Alternatively the routing predictor may take into account the route indicated in the guidance mode and the recoded previous routes together. For example, a guidance mode route may provide an alternative route to a previously visited location or may terminate at an endpoint near a previously visited location. In such circumstances, the routing predictor may predict that the previously recorded route is actually more likely than the guidance mode route and may make a prediction accordingly.

The predicted route determined by the routing predictor 23 is provided to a mapping unit 25. The mapping unit 25 also receives the current position information from the GNSS receiver 21. The mapping unit 25 compares the predicted route to mapped signal strength information retrieved from a mapped signal strength store 27. The mapped signal strength store 27 contains various data that link geographic positions to measured signal strength for the mobile telephone network at those positions. Signal strength can be stored in terms that the mapping unit and data controller will be able to make use of, for example as RSSI (received signal strength indicator) values. RSSI or a similar approach can be used with mobile telephone systems and other wireless communication technologies. Thus the mapping unit 25 can determine predicted signal strength for the predicted route.

This predicted signal strength can include either or both of positions of predicted signal strength and predicted times of predicted signal strength. The positions of predicted signal strength are derived from comparison between the predicted route and the mapped signal strength information. The predicted times of predicted signal strength are derived from the positions of predicted signal strength and information relating to expected time to arrival at the various positions and thus express the predicted times in terms of predicted durations of the predicted signal strengths along the predicted route.. The expected time of arrival information can be determined from known speed limits for the roads in the predicted route received from the routeing predictor 23 and/or can take into account a present speed of travel of the vehicle 1, and/or can take into account traffic speed information received using a radio traffic information receiver (not shown) such as a RDS-TMC (radio data system -traffic message channel) receiver or DAB radio traffic receiver (such as using TMC over DAB or using a TPEG -traffic protocol experts group -approach). Traffic information may also be received over the mobile telephone network via the network access device 31.

The mapping unit 29 may additionally make use of time of day information to further refine the predicted signal strength along the predicted route. This can be performed regardless of whether time of day has been taken into account by the routing predictor 23. Although in many wireless infrastructures across a geography, the actual signal strength is unlikely to vary significantly as a function of time of day, the time of day may have an impact of predicted speed of travel along the predicted route and thus may impact the length of time for which the vehicle will experience the different predicted signal strength levels as it travels along the route. For example, during known peak road travel periods the expected speed of travel may be reduced (thus causing geographic regions of a given signal strength to be traversed more slowly) and during known quiet road travel periods (such as the early hours of the morning) the expected speed of travel may be increased.

The mapping information in the mapped signal strength store 27 may additionally be utilised by the mapping unit 29 to compare with the current location as provided by the GNSS receiver 21 and the predicted route from the routing predictor 23 to determine an expected rate of change of signal strength over an upcoming portion (or the whole) of the predicted route. If this comparison reveals a predicted rapid drop in signal strength then a prediction of fast fade has been made. This prediction of upcoming fast fade can be used in addition to the predicted times and/or locations of signal strength.

Where current and/or predicted vehicle speed is taken into account, this can additionally or alternatively be used to assist with a predicted rate of change of signal strength. This can therefore provide, for example, that although slow fade is recorded in the stored mapping information as a rate of change by distance, during high vehicle speed this slow fade may in effect become fast fade. Thus a further refinement can be provided to the determination of a fast fade condition.

Conversely, the rate of change of signal strength may indicate when moving from a low signal strength area to a high signal strength area the rate at which signal strength is likely to reach usable signal strength levels. Thus the rate of change of signal strength may be taken into account for both fade-out and fade-in of signal strength.

The predicted signal strength and optionally a predicted rate of change of signal strength is then provided by the mapping unit 25 to a data controller 29. The data controller 29 controls the timing for transmission of and requesting reception of data over the mobile telephone network for services required either by the systems of the vehicle 1 or as requested via the user interaction device 7. Thus the data controller 29 can use the predicted signal strength and optionally also the predicted fade rate (rate of change of signal strength) to determine appropriate times to make data transmissions and request reception of data transmissions, particularly such data transmissions that are not time-critical. In some example, the controller can also reference the current measured signal strength to check whether an area of good signal has actually occurred. For example a cross-check could be made between a prediction of good signal strength and such good signal strength actually occurring. Thus the data controller could take account of situations such as a failed telephone network antenna which causes a lower signal strength than is predicted from the stored mapping information.

Where predicted times (as a function of journey time along the predicted route) of predicted signal strength are generated, these can additionally be utilised by data controller 29 to further refine the control of data transmission. This allows the data controller 29 to take into account a volume of data for transmission and an expected duration for that transmission such that the data controller 29 may determine that a given transmission should only commence if there is predicted to be good enough signal strength for a long enough time duration that the transmission can be expected to complete within the confines of a single region of good signal strength. Similar processing can also take place in the case of or additionally take into account expected durations of poor and good signal strength derived from speed of travel predictions determined upon the basis of traffic information and/or time of day information as discussed above.

Where time of day information is available, this may have an impact of expected cell loading of the mobile telephone network and/or expected atmospheric influences on the thus may have an impact on the available data rate over the mobile telephone network. For example, during known times of peak vehicle traffic, it may be expected that multiple vehicles in a small area will simultaneously be calling upon the mobile telephone network for data capacity and as a result the per-device data rate availability may be low. Likewise, during times of concentrated demand on the mobile telephone network, the effective range of each wireless infrastructure antenna 11 may be reduced due to a large number of devices all attempting to connect via that antenna and those devices further from the antenna suffering one or both of reduced data rate and reduced availability of connection. Time of day may also be used to predict atmospheric effects such as morning fog which may attenuate mobile telephone signals and thus have an impact on achievable data rates. The data controller 29 can thus use the time of day information to further refine the control of data transmission based upon predictions of how time of day is expected to impact data transmission over the mobile telephone network.

Therefore, under control of the data controller 29, the network access device 31 is controlled to transmit and receive data over the mobile telephone network, at times and locations that at chosen based upon the combination of the predicted route and the mapped signal strength information.

An example of transmission activity over a route portion is further illustrated with reference to Figure 4. In this figure, the route portion has 14 positions as the route passes through an example geography. For each location, an example value of predicted signal strength (RSSI) and predicted fade type is indicated, along with an example corresponding data transmission state (Tx or pause). This illustrates that both predicted signal strength and fade type can be taken into account in determining whether to conduction transmission or to pause transmission.

In the example of Figure 14, it will be seen that initially (locations 1-3) the signal strength (RSSI) is predicted to be good and the fade is predicted to be slow such that data transmission is scheduled to be enabled. Then, as the route proceeds to location 4, the signal strength is predicted to drop and fast fade is predicted to occur. Thus data transmission is scheduled to be paused. The pause state continues through locations 5 and 6, where the signal strength is predicted to remain poor and fast fade is predicted to occur before transmission is scheduled to be resumed at location 7 where the signal strength is predicted to rise to an acceptable level despite the presence of fast fade. The data transmission remains scheduled to be active as the route continues through locations 8 to 14, despite the predicted presence of various slow and fast fade conditions as the signal strength is predicted to remain sufficient over that portion of the route.

As has been mentioned above, the mapped signal strength information stored in the mapped signal strength information store 27 may be learned mapping and signal reception conditions gathered on previous journeys and/or may be reception maps collected by external providers. Where the system gathers signal strength conditions to create, modify, supplement or update stored maps (whether the stored maps arise from previous gathering of information from previous journeys, maps collected by external providers or a combination of the two), the mapping unit 25 can use position information from the GNSS receiver 21 and signal strength information from the network access device 31 to record the signal strength information in combination with the corresponding location to the mapped signal strength store 27.

Thus it will be understood that a combination of known signal strength characteristics across a geography and prediction of a route through the geography can be used to predict appropriate data transmission active and pause times so as to optimise power utilisation for data transmission to occur at those times that the data transmission can be carried out efficiently at low power operation levels.

In the example system illustrated above with respect to Figure 3, the system can be considered as having five states: initial, mapping, data transaction, inactive and shutdown. These states and the movement paths between states are illustrated in Figure 5.

In the initial state the algorithm is awaiting the trigger of vehicle ignition (alternatively some other power activation trigger) to go into the mapping state. The mapping state is the main active state (at least in deployments where the system creates or updates the mapped signal information on an ongoing basis) where the system uses received signal strength information from the network access device 31 and the position information from the GNSS receiver 21 signals to create and/or update the stored records of the mapped network signal strength.

When an application or service in the vehicle 1 requires a data transmission to be made, the system enters the data transaction state. In this state the system uses the mapped signal strength information along with predictive route data to decide when to send/receive data or to pause the data request. Once the data handling to complete the data transmission has been completed, the system returns to the mapping state. In some examples, the system may be configured to carry on recording the mapped signal strength information while the data transaction state is active.

In order to take account of priority requests for use of the network access device, an over-ride can be applied to place the system into an inactive state. In the present example, priority requests for network access device access can include making a call to emergency services (eCall) and communication relating to stolen vehicle tracking (SVT). Other priority requests could relate, for example, to voice call traffic in general. Thus from either the mapping state or the data transaction state, a priority request for network access device (illustrated in Figure 5 as being an eCall or SVT) causes the current active state to be suspended and the inactive state to be entered. Once the priority request situation has ended, the previous state can be resumed.

Finally, when a termination trigger is received, such as the ignition being turned off (or other power termination trigger), the system enters shutdown state. This provides for all data collected by the system (such as new mapping of signal strength information) to be written to memory before the system finally powers-down. This state can be entered from either the mapping state or the data transaction state. Handling of an ignition off condition while a priority request activity is in progress is a matter for the priority request handling mechanism and not an issue for the system of the present examples. Should an end condition for a priority request occur, to cause the system to return to the mapping or data transaction state, after the ignition has been turned off, the system would enter the shutdown state.

As shown in Figure 6, the behaviour of the mapping unit is also illustrated. As shown, the mapping unit sits in an idle state until signal strength and position information are both being received. At this point, the mapping unit loops storing the signal strength information in associate with the position information to the mapped signal strength store. If the position and/or signal strength information ceases arriving, the mapping unit then returns to the idle state. In this example, the storing loop ends when either the ignition is turned off (shutdown) or when a data request is received (data transaction state). As noted above, in some examples, the system may be configured to allow the storing loop to continue operation while a data transmission is being handled by the data transaction state. This may take the form of repeated transitions between the mapping state and the data transaction state or by allowing both states to exist simultaneously.

As will therefore be appreciated, the system of the present teachings can use the position information to map signal strength while the vehicle drives around a geography and thereby create a learned record of signal strength across the geography. This recorded signal strength mapping is combined with route prediction such that when the route prediction foresees an upcoming area of poor reception then the data transaction state can pause the transmission/reception of data until an area predicted to have better reception is reached.

Using this approach, when a data transmission is requested by an application or service running in the vehicle, that data transmission will be queue or buffered until such a point that it can be transmitted again.

Accordingly, power usage by a network access device of the vehicle can be managed to optimise power use, by waiting until the vehicle is in an area predicted to have good signal coverage and hence requiring a low transmission power to send data and communicate with the network. This also provides for reducing a number of retries for data transmission as data transmission is attempted in strong reception areas.

Therefore, from one perspective, there can be provided apparatus for managing power usage of an in-vehicle data connectivity device, the apparatus comprising: storage configured to hold mapping data that links known locations to observed wireless data signal strength; and a controller configured to use the mapping data and a prediction of an expected route to predict when the vehicle will enter into areas of high or low wireless data signal strength and to use the prediction to choose when to make and pause data communications.

The system illustrated above can be implemented as an add-on module in software, hardware and/or firmware. In some examples, the system can be implemented as an add-one module for a vehicle already having a satellite navigation unit and a network access device. Thus, from one perspective, there has now been described a system that uses predicted routing together with mapped signal strength information to provide for intelligent active power management. By this approach, data communications can be paused when about to enter poor/no reception areas such that power usage by an in-vehicle network access device can be minimised by avoiding a situation where the network access device increases power to attempt to attain a stable connection. by application of such intelligent active power management, average data rates achieved by the in-vehicle network access device can be maintained or even improved relative to just allowing the network access device to attempt data transmissions without reference to the predicted routing and signal strength mapping. For example, by using appropriate buffering to optimise use of predicted good signal areas the system will be able to buffer up more data in good reception areas to offset poor reception areas and hence provide smoothing of the overall network performance. Thus average data transfer rates may be kept higher and user experience may be improved.

The subject matter of all combinations of independent and dependent claims, both singly and multiply dependent, is expressly contemplated but is not necessarily described in detail for the sake of brevity. Additionally, any feature discussed in a claim in a first category is intended to be explicitly disclosed for any other type of claims having corresponding features. For example, features discussed in a dependent apparatus claim are also considered as relevant and disclosed in respect of a corresponding method. The present disclosure has been described in an illustrative manner, and it is to be understood that the terminology used herein is intended to be descriptive rather than limitative, modifications and variations of the present disclosure are possible in light of the above teachings, and the disclosure may be practiced otherwise than as specifically described in respect of example implementations. In particular the present disclosure is intended to include any possible combination of one or more features discussed in any part of the description, drawings and/or claims with one or more features discussed in any other part of the description, drawings and/or claims, provided that the combination can be done technically.

When a method is discussed in the present disclosure with steps carried out in a specific order, it is within the scope of the present disclosure that method steps may be carried out in any other order and/or in parallel, provided that the change of order is technically achievable.

For the ease of representation and of discussion, some of the elements of the present disclosure have been described as separate logical elements. This representation is however not intended to be limiting for the physical implementation of these elements and two or more elements may for example be implemented in the form of a single hardware and/or software element which is configured to provide the funcfionalifies of the two or more elements.

Likewise, a single element may be implemented using two or more hardware and/or software elements together providing the same functionalities of the single element (e.g. a controller may comprise a CPU, a plurality of CPUs or a plurality of CPU cores which are operable to carry out instructions, for example from a computer program). Generally, any suitable physical implementation corresponding to the logical elements discussed herein and providing the functions or features discussed herein are intended to be fully within the scope of the present

disclosure.

Also, the representations of apparatuses provided herein are not intended to be exhaustive or limiting and these apparatuses may include fewer or additional elements. The term "or" is intended to explicitly disclose both an exclusive or and a non-exclusive choice and the expression "and/or" is sometimes used to emphasise that both exclusive and non-exclusive options are considered.

As used in the present disclosure, the singular forms "a" "an" and "the" are intended to include plural references unless expressly and unequivocally limited to the singular form. In turn, the expression "one or more" is intended to encompass "one" and "a plurality of".

As used herein, the terms "include" and "comprise" are intended to be non-exhaustive inclusion, such that one or more items which are included or comprised in a list do not necessarily limit the list to these items only to the exclusion of other items. For example, only these items or these and additional items may be included in the list.

As used herein, the terms "based on [something are intended to mean "based at least on [something and while it expressly disclose using this "something" only, it is not intended to provide an exhaustive list and additional aspects or parameters may also be taken into account.

The foregoing description is intended to be illustrative in nature but should not be used to limit the scope afforded. Rather, the scope of protection afforded is to be determined from an understanding of the true spirit and scope of the appended claims.

Claims

CLAIMS1. Apparatus for managing power usage of an in-vehicle data connectivity device, the apparatus comprising: storage configured to hold mapping data that links known locations to observed wireless data signal strength; and a controller configured to use the mapping data and a prediction of an expected route to predict when the vehicle will enter into areas of high or low wireless data signal strength and to use the prediction to choose when and/or how to make data communications.
2. The apparatus of claim 1, wherein the controller is configured to use the prediction to choose when to make or pause data communications.
3. The apparatus of claim 1 or 2, wherein the in-vehicle connectivity device is configured to provide data connectivity via a mobile telephone network and wherein the wireless data signal strength is a signal strength indicator of the mobile telephone network.
4. The apparatus of claim 1, 2 or 3, wherein the wireless data signal strength is a received signal strength indicator.
5. The apparatus of any preceding claim, further comprising a satellite navigation system receiver for providing information relating to position of the vehicle.
6. The apparatus of claim 5, further comprising a routing predictor configured to produce the prediction of an expected route based information relating to position of the vehicle obtained from the satellite navigation receiver.
7. The apparatus of claim 6, wherein the routing predictor is configured to produce the prediction of an expected route based upon one or more selected from the group comprising: comparison of a present journey to a journey history; and routing guidance instructions to a selected destination.
8. The apparatus of any preceding claim, wherein mapping data held in storage is received from an external mapping data source.
9. The apparatus of any preceding claim, wherein the controller further comprising a mapping unit configured to associate a measured wireless data signal strength to a position of the apparatus at which the measured wireless data signal strength was taken and to store the associated location and measured wireless data signal strength as mapping data in the storage.
10. The apparatus of claim 9, wherein the associated location and measured wireless data signal strength are stored as an update to mapping data previously stored to the storage by the mapping unit.
11. The apparatus of claim 9 as dependent upon at least claim 8, wherein the associated location and measured wireless data signal strength are stored as an update to mapping data received from an external mapping data source.
12. The apparatus of any preceding claim, wherein the controller is configured to control making and pausing data communications by controlling a wireless transceiver between active and inactive states.
13. The apparatus of any preceding claim, wherein the controller is configured to use the mapping data and prediction of an expected route to predict a rate of change of signal strength and to use the prediction to choose when and/or how to make data communications.
14. The apparatus of claim 13, wherein the controller is configured to additionally use predicted vehicle speed over the expected route to predict the rate of change of signal strength.
15. A method for managing power usage of an in-vehicle data connectivity device, the method comprising: using mapping data that links known locations to observed wireless data signal strength and a prediction of an expected route to predict when the vehicle will enter into areas of high or low wireless data signal strength; and using the prediction to choose when and/or how to make data communications.
16. The method of claim 15, further comprising using the prediction to choose when to make or pause data communications.
17. The method of claim 15 or 16, wherein the in-vehicle connectivity device is configured to provide data connectivity via a mobile telephone network and wherein the wireless data signal strength is a signal strength indicator of the mobile telephone network.
18. The method of claim 15, 16 or 17, wherein the wireless data signal strength is a received signal strength indicator.
19. The method of any of claims 15 to 18, further comprising obtaining information relating to position of the vehicle using a satellite navigation system receiver.
20. The method of claim 19, further comprising producing the prediction of an expected route based information relating to a position of the vehicle obtained from the satellite navigation receiver.
21. The method of claim 19, wherein the producing of an expected route is based upon one or more selected from the group comprising: comparing a present journey to a journey history; and referring to routing guidance instructions to a selected destination.
22. The method of any of claims 15 to 21, further comprising receiving mapping data from an external mapping data source.
23. The method of any of claims 15 to 22, further comprising: associating a measured wireless data signal strength to a position of the apparatus at which the measured wireless data signal strength was taken; and storing the associated location and measured wireless data signal strength as mapping data.
24. The method of claim 23, wherein the storing comprises storing the associated location and measured wireless data signal strength as an update to mapping data previously stored.
25. The method of claim 23 as dependent upon at least claim 22, further comprising storing the associated location and measured wireless data signal strength as an update to mapping data received from an external mapping data source.
26. The method of any of claims 15 to 25, further comprising controlling making and pausing data communications by controlling a wireless transceiver between active and inactive states.
27. The method of any of claims 15 to 26, further comprising using the mapping data and prediction of an expected route to predict a rate of change of signal strength and using the prediction to choose when and/or how to make data communications.
28. The method of claim 27, further comprising using predicted vehicle speed over the expected route to predict the rate of change of signal strength
29. Apparatus substantially as hereinbefore described, with reference to any of the accompanying Figures.
30. Method substantially as hereinbefore described, with reference to any of the accompanying Figures.