GB2579346A

GB2579346A - Vehicle control system and method

Info

Publication number: GB2579346A
Application number: GB1818541.3A
Authority: GB
Inventors: Hussein Adwan Adam
Original assignee: Jaguar Land Rover Ltd
Current assignee: Jaguar Land Rover Ltd
Priority date: 2018-11-14
Filing date: 2018-11-14
Publication date: 2020-06-24
Anticipated expiration: 2038-11-14
Also published as: GB2579346B; GB201818541D0

Abstract

A control system and method for a host vehicle operable in an autonomous mode comprises processing information indicative of a pattern of use of the host vehicle; and cause downloading of dynamic map data and/or dynamic traffic data from a remote information source in dependence on the processing. Data download is scheduled in dependence on the processing, wherein the download schedule is a time and/or a location of the host vehicle, at which the download is to commence or not commence. Availability of network coverage at the particular time or location; an indication of past successful downloads at the particular time or location; or a characteristic indicative of a time taken to perform the download, at the particular time or location, are all conditions considered for scheduling a download. At least one path planning algorithm of the host vehicle is configured to use the dynamic map and traffic data. Dynamic map data comprises information on at least: roadworks; lane closures; speed limits; weather conditions; road surface conditions, and the dynamic traffic data comprises information on: traffic conditions; an emergency vehicle location. The speed and/or path of the vehicle in the autonomous mode is appropriate to a driving context.

Description

VEHICLE CONTROL SYSTEM AND METHOD

TECHNICAL FIELD

The present disclosure relates to a vehicle control system and method. In particular, but not exclusively it relates to a vehicle control system and method for a vehicle operable in an autonomous mode.

Aspects of the invention relate to a control system, a method, a vehicle, computer software, and a non-transitory computer-readable storage medium.

BACKGROUND

It is known for a vehicle to host a system that enables the host vehicle to operate in accordance with a predefined autonomous mode. The host vehicle may be instructed to operate in accordance with the predefined autonomous mode by a user (occupant) of the host vehicle i.e. via an input device at which a user input is received to control operation of the predefined autonomous mode.

The occupant may desire for the speed and path of the host vehicle in the autonomous mode to be appropriate to a driving context. The driving context may relate to factors such as the environment outside the host vehicle. The environment includes infrastructure and other road users (ORUs). The driving context may relate to the specific preferences of the occupant. The driving context may relate to the condition of the host vehicle.

It is an aim of the present invention to address disadvantages of the prior art.

SUMMARY OF THE INVENTION

Aspects and embodiments of the invention provide a control system, a method, a vehicle, computer software, and a non-transitory computer-readable storage medium.

According to an aspect of the invention there is provided a control system for a host vehicle operable in an autonomous mode, the control system comprising one or more controllers, the control system configured to: process information indicative of a pattern of use of the host vehicle; and cause downloading of dynamic map data and/or dynamic traffic data from a remote information source in dependence on the processing.

This advantageously improves the likelihood of success or reduces the likelihood of failure of the download. For example, the downloads could be scheduled to avoid locations and/or times of inhibited connectivity. Fewer wasted download attempts results in less energy usage and less data usage. Further, more up-to-date dynamic data may result in a more reliable autonomous mode.

The one or more controllers may collectively comprise: at least one electronic processor having an electrical input for receiving the information; and at least one electronic memory device electrically coupled to the at least one electronic processor and having instructions stored therein; and wherein the at least one electronic processor is configured to access the at least one memory device and execute the instructions thereon so as to cause the host vehicle to perform the processing and the causing downloading The dynamic map data and/or dynamic traffic data download may be scheduled in dependence on the processing. The download schedule may be a time and/or a location of the host vehicle, at which the download is to commence or not commence.

The control system may be configured to determine a time and/or a location, at which a condition associated with downloading dynamic map data and/or dynamic traffic data is satisfied or not satisfied.

The satisfaction or non-satisfaction of the condition at a particular time or location may be determined in dependence on information indicative of at least one of: availability of network coverage at the particular time or location; an indication of one or more past successful downloads at the particular time or location; or a characteristic indicative of a time taken to perform the download, at the particular time or location.

The dynamic map data and/or dynamic traffic data download may be scheduled to commence before a time or before the host vehicle reaches a location, associated with non-satisfaction of the condition, or wherein the downloading may be scheduled to commence at a time or at a location of the host vehicle associated with satisfaction of the condition.

The dynamic map data and/or dynamic traffic data download may be at least partially over a cellular network while the host vehicle is being driven.

At least one path planning algorithm of the host vehicle may be configured to use the dynamic map data and/or dynamic traffic data when planning a path of the host vehicle during autonomous driving in the autonomous mode.

The information may comprise an indication of a location at which the host vehicle has previously been and/or may be indicative of a temporal pattern of use of the host vehicle.

The dynamic map data and/or dynamic traffic data download may be scheduled to commence in dependence on an expected route and/or destination and/or timing of use of the host vehicle as determined by the processing of the information, without a navigation system of the host vehicle having received a user navigation input comprising a location and/or a route.

The dynamic map data and/or dynamic traffic data dynamically may update periodically, wherein the period may be from the range of a plurality of minutes to one or more months.

The dynamic map data may comprise information on at least one of: roadworks; lane closures; speed limit changes; weather conditions; road surface conditions, and/or the dynamic traffic data may comprise information on at least one of: traffic conditions; an emergency vehicle location.

According to another aspect of the invention there is provided a method for controlling a host vehicle operable in an autonomous mode, the method comprising: processing information indicative of a pattern of use of the host vehicle; and causing downloading of dynamic map data and/or dynamic traffic data from a remote information source in dependence on the processing.

According to a further aspect of the invention there is provided a vehicle comprising any one or more of the control systems described herein.

According to a further aspect of the invention there is provided computer software that, when executed, is arranged to perform any one or more of the methods as described herein.

According to a further aspect of the invention there is provided a non-transitory, computer-readable storage medium storing instructions thereon that, when executed by one or more electronic processors, causes the one or more electronic processors to carry out any one or more of the methods as described herein.

Within the scope of this application it is expressly intended that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and/or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. That is, all embodiments and/or features of any embodiment can be combined in any way and/or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and/or incorporate any feature of any other claim although not originally claimed in that manner.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Fig 1 illustrates an example of a host vehicle; Fig 2A illustrates an example of an electronic controller; Fig 2B illustrates an example of a computer-readable storage medium; Fig 2C illustrates an example of a system; Fig 3 illustrates an example of a method; Fig 4 illustrates an example of a method; and Fig 5 illustrates an example of a method.

DETAILED DESCRIPTION

Fig 1 illustrates an example of a vehicle 10 in which embodiments of the invention can be implemented. In some, but not necessarily all examples, the (host) vehicle 10 is a passenger vehicle, also referred to as a passenger car or as an automobile. Passenger vehicles generally have kerb weights of less than 5000 kg. In other examples, embodiments of the invention can be implemented for other applications, such as industrial vehicles.

The host vehicle 10 may comprise any appropriate prime mover (not shown) or a plurality of prime movers. An example of a prime mover is an internal combustion engine.

Another example of a prime mover is an electric motor. The vehicle may be an electric vehicle or a hybrid-electric vehicle.

The host vehicle 10 may be operable in an autonomous mode. The host vehicle 10 may also be operable in a non-autonomous mode.

A control system 200 is shown in Fig 2A which may implement, at least in part, the functionality of the autonomous mode. The control system 200 may implement, at least in part, the functionality of the non-autonomous mode. The control system 200 may comprise means to cause any one or more of the methods described herein to be performed, at least in part.

The control system 200 may comprise one or more (electronic) controllers 202. One controller 202 is shown in Fig 2A.

The controller 202 of Fig 2A includes at least one electronic processor 204; and at least one electronic memory device 206 electrically coupled to the electronic processor 204 and having instructions 208 (e.g. a computer program) stored therein, the at least one electronic memory device 206 and the instructions 208 configured to, with the at least one electronic processor 204, cause any one or more of the methods described herein to be performed.

The control system 200 may be supplied separately from or together with any input devices and any actuators controlled by the control system 200.

Fig 2B illustrates a non-transitory computer-readable storage medium 210 comprising the computer program 208 (computer software).

Fig 2C shows an example of a system 300 for a vehicle such as the host vehicle 10 of Fig 1.

The system 300 may implement, at least in part, the functionality of the autonomous mode.

The system 300 comprises the control system 200. The system 300 may comprise one or more actuators for operation by at least the control system 200 in at least the autonomous mode. The actuators may be operably (directly or indirectly) coupled to one or more outputs of one or more controllers of the control system 200.

The actuators may comprise one or more torque control actuators. The torque control actuators are for controlling torque received at one or more road wheels of the host vehicle 10.

The torque control actuators may comprise a brake control actuator 316.

The brake control actuator 316 comprises any appropriate means for controlling a negative torque received by road wheels of the host vehicle 10.

In an implementation, the brake control actuator 316 may comprise a friction brake actuator for applying friction brakes of the host vehicle 10.

The brake control actuator 316 may be operated in dependence on an output signal such as a brake demand signal output from the control system 200, in the autonomous mode.

The torque control actuators may comprise an acceleration control actuator 312.

The acceleration control actuator 312 comprises any appropriate means for controlling a positive torque received by road wheels of the host vehicle 10, for instance means for controlling a torque output of the prime mover.

In an implementation, the acceleration control actuator 312 may comprise a throttle position actuator for controlling an opening degree of a throttle for an internal combustion engine.

The acceleration control actuator 312 may be operated in dependence on an output signal such as a torque demand signal output from the control system 200, in the autonomous mode.

The actuators may comprise a steering control actuator 314. The steering control actuator is part of a steering subsystem of the host vehicle 10, for controlling the direction of the host vehicle 10.

The steering control actuator 314 comprises any appropriate means for controlling a direction of the host vehicle 10, for instance means for controlling a steering angle of front road wheels of the host vehicle 10.

In an implementation, the steering control actuator 314 may comprise a motor for actuating a steering rack of the host vehicle 10. Additionally or alternatively, the steering control actuator 314 may comprise a friction brake actuator, configured to control a braking torque differential between left and right wheels of the host vehicle 10.

The steering control actuator 314 may be operated in dependence on an output signal such as a steering signal output from the control system 200, in the autonomous mode.

One or more of the actuators 312, 314, 316 may be operable automatically by the control system 200 in the autonomous mode. One or more of the actuators may be operable under manual control by a vehicle occupant in the non-autonomous mode.

The system 300 may comprise one or more input devices 304, 306, 308, 310. The input devices may be coupled to one or more inputs of one or more controllers of the control system 200.

The signals to the actuators may be dependent on signals from the input devices.

The input devices may comprise sensing means 306, 308, 310, such as one or more sensor units. The sensing means may enable machine vision for autonomous driving.

The sensing means outputs to the control system 200 environment information indicative of the environment in the vicinity of the host vehicle 10. The environment information is indicative of one or more environment characteristics, e.g. road type, presence of other road users, road markings, road priorities, etc. The sensing means may be configured for or suitable for attachment to the host vehicle 10.

The sensing means may comprise an optical sensor such as a (visual) camera 308. An optical sensor is for imaging in the visible light spectrum.

The sensing means may comprise range detection means 310. The term "range detection means" will be understood to mean any sensing means for detecting sensor data indicative of a range of a target object from the host vehicle 10. The range detection means 310 may comprise a rangefinder. The range detection means 310 may comprise a laser rangefinder. The laser rangefinder may comprise a lidar sensor. The control system 200 with at least one of the sensing means may be arranged to capture a doppler shift in an emitted signal. The sensing means may comprise a radar sensor 306. The sensing means may comprise an ultrasound sensor (not shown).

The system 300 may comprise a plurality of the input devices, each input device representing a different sensing modality. For example, the system 300 may comprise lidar sensors, radar sensors and cameras. This redundancy improves safety and enables autonomous driving in various environments such as driving at night or through fog.

The sensing means may be capable of detecting objects within a first sensing range. The first sensing range may be, at most, a maximum line of sight distance from the sensing means. The first sensing range may be from approximately 80m to approximately 100m from the location of the sensing means.

Objects may be recognised by a classification process (algorithm) of the control system 200. Objects which may be classified may include one or more of: automobiles; heavy goods vehicles; motorcycles or pushbikes; emergency services vehicles; road signs and their instructions (including temporary street furniture such as traffic cones); and road markings and their instructions. The locations of the objects may be determined, for example using range detection means 310. Which lane the objects are in may be determined. A relative speed between the host vehicle 10 and an object may be determined, which may indicate whether a separation (also referred to as headway, inter-vehicular distance, following distance) from the object is increasing or decreasing and at what rate. The movement of the objects may be tracked using optical flow analysis for example.

The sensing means collectively provide a field of view around the host vehicle 10. The field of view may extend 360 degrees horizontally around the host vehicle 10 or less. The collective field of view also extends vertically by any appropriate amount. The individual sensor units may be located at the front, rear and/or sides of the host vehicle 10. Sensor units may be located at corners of the host vehicle 10. Sensor units may be located on wing mirrors of the host vehicle 10. Some sensor units may be located high on the host vehicle 1 0, such as above the waist of the host vehicle 10. Some sensor units may be at bumper height or lower.

The input devices may communicate with the control system 200 using any appropriate electronic communication network. Similarly, the actuators may be configured for drive-by-wire operation, therefore communication between the control system 200 and the actuators may also be via any appropriate electronic communication network. Redundancy may be provided by implementing multiple communication networks and/or backup controllers in the control system 200 and/or backup power supplies coupled to independent power sources (e.g. batteries). Example communication networks include a Controller Area Network (CAN), an Ethernet network, a Local Interconnect Network, a FlexRay(TM) network or the like.

The system 300 may comprise a telematics unit 304. The telematics unit 304 may comprise one or more controllers. The telematics unit 304 may be a telematics control unit (TCU). The illustrated TCU does not form part of the control system 200 but it may do in other examples.

The TCU may be configured at least to function as a vehicle software update client. The TCU may comprise an antenna arrangement. The antenna arrangement may be configured as a receiver, a transmitter or as a transceiver. This enables software updates to be obtained from a remote (offboard) information source 302 such as a server, another vehicle according to a vehicle-to-vehicle (V2V) communication model, or external infrastructure according to a vehicle-to-infrastructure (V2I) communication model.

The TCU may be configured to download software-over-the-air (SOTA) updates for installation in the host vehicle 10. Software components for SOTA updates could include at least one of: executable code, configuration data, graphics, map data, dynamic data such as dynamic map data and dynamic traffic data and weather data, audio calibration, multimedia, and firmware.

SOTA updates are received via a wireless communication network, such as a cellular network. The host vehicle 10 may subscribe to a cellular network service. The TCU may comprise a subscriber identity such as an international mobile subscriber identity (IMSI) number, to facilitate access to the cellular network. A subscriber identity module (SIM) may be installed in the host vehicle 10 to enable the TCU to access the IMSI and therefore the cellular network. An operator of the cellular network may associate the IMSI with a customer account and bill the customer for data usage and/or access to the cellular network. Additionally or alternatively, the TCU may comprise means to access a short-range communication network such as a wireless local area network or a wireless personal area network. The TCU may comprise means, such as a universal serial bus interface, for wired communication with the remote information source 302.

Advantageously, SOTA functionality enables the dynamic data to be downloaded while the host vehicle 10 is undergoing a journey. This enables substantially live updates. The telematics unit 304 may be configured to schedule the SOTA downloads from the remote information source 302 according to push or pull methods. Client-server, V2V and/or V2I communication models could be used. The telematics unit 304 may be configured to perform the downloads periodically at a predetermined interval which may depend on the download payload. For instance, the interval for downloading dynamic traffic data may range from the order of minutes to the order of hours. The interval for downloading dynamic map data may range from the order of minutes to the order of months. The interval for downloading non-dynamic data may range from the order of months to the order of years, or it may need to be manually updated at a dealership.

Dynamic traffic data as described above may be obtained via a SOTA update and/or a service provider application programming interface. Dynamic traffic data comprises substantially live information on traffic conditions. For example, the dynamic traffic data may indicate slow moving or stopped traffic. The dynamic traffic data may be associated with one or more metrics associated with traffic density, flow rate, speed, inter-vehicular distance, or journey time. The metrics may indicate a current condition, a change, or an expected condition. The metrics may be associated with particular locations and/or with particular times. Falling speeds/flow rates/inter-vehicular distances and rising densities/journey times are indicators of traffic conditions.

The dynamic traffic data enables a traffic condition to be determined. The traffic condition could be determined by comparing a current condition with a change or expected condition. A traffic condition could be determined when at least one threshold is passed such as an absolute or relative threshold. The relative threshold could be a statistical significance threshold, for example.

The dynamic traffic data may have sufficient resolution, granularity and/or detail to enable the traffic condition to be associated with a specific lane of a highway, from a plurality of lanes for travel in a same direction. This enables certain lanes to be avoided before a traffic queue is reached.

Dynamic map data as described above may comprise information that enables map data stored onboard the host vehicle 10 to be supplemented. The map data may be used by the control system 200 and/or a navigation subsystem of the host vehicle 10 for route planning.

Map data indicates at least roads and junctions. Locations may be indicated by map data via global position coordinates. The navigation subsystem may be configured to receive user navigation inputs defining navigation constraints. Navigation constraints may comprise one or more of a destination, a waypoint, a navigation route or acceptable routes, an avoidance setting (e.g. avoidance of toll roads), a target to be reduced/minimised such as minimum distance or minimum travel time, or a target to be achieved such as a time of departure or arrival. Once a navigation route has been selected, the selected navigation route may impose navigation constraints on the autonomous mode, to enable autonomous navigation.

The dynamic map data and dynamic traffic data may be compatible with said map data. Dynamic map data may comprise indications of at least one of the following conditions: traffic conditions such as roadworks and/or lane closures; speed limit changes such as variable speed limit changes imposed by permanent variable speed limit systems; weather conditions; or road surface conditions. Examples of roadworks include road closures, lane closures and traffic diversion routes. Examples of lane closures include blocked lanes, whether caused by roadworks, broken down vehicles or other causes. Examples of road surface conditions include potholes, loose or broken surface material, low friction hazards (e.g. ice or spilled liquids), or objects in the road (e.g. lost cargo). The indications may specify one or more locations such as where the condition starts and/or ends. The indications may specify which lane or lanes the condition applies to. The indications enable certain lanes or roads to be avoided before a traffic queue is reached. The above indications may be available by analysis of data from the sensing means, however for a much shorter range. Indications from multiple sources, such as the dynamic map data and the sensing means, may be combined to improve certainty.

The map data, dynamic map data and/or dynamic traffic data may comprise a fine level of granularity. For example, the individual lanes for travel in a same direction on a highway may be distinguishable. The map data and/or dynamic map data may comprise a high level of detail. For example, indications of road markings and/or road sign (traffic sign) information may be distinguishable from the data. Distinguishable road markings may comprise indications of lane boundaries. Distinguishable lane boundaries may be indicated by lane boundary markings in the data or may be indirectly indicated by lane centre position information in the data. The map data and/or dynamic map data may be of any suitable format that enables an identification of an instruction regarding a lane, a junction, a right of way (priority) or caution.

The control system 200 may further be configured to determine a highway law applicable to the host vehicle's current location and/or to a planned location or route of the host vehicle 10. The control system 200 may be configured to apply information associated with the applicable highway law to correctly identify instructions from the map data and/or dynamic map data. For example, if a planned route is in the United Kingdom the control system 200 may be configured to recognize road markings or traffic (road) sign information in a manner that corresponds to the requirements of the Highway Code. This is advantageous because the same road markings or signs can have different legal meanings in different highway jurisdictions.

The additional detail from the map data and/or dynamic map data may enable not only improved route planning by a navigation subsystem, but also improved path planning for the autonomous mode. For example, the control system 200 may process the map data and/or dynamic map data to determine which lanes the host vehicle 10 will travel on at which points on a journey. The control system 200 may further determine when lane changes may need to occur as directed by road signs or other information from the data. Certain lanes can be avoided or moved out of before a traffic queue is reached. Further, the dynamic data may define a second sensing range of machine vision, farther than the first sensing range. For example, the dynamic data may at least cover an entire route planned by the navigation subsystem and may cover one or more alternative routes in case of a later route recalculation. This enables certain lanes or roads to be avoided. The dynamic data may cover a regional, national or even international area. However, a greater coverage area may adversely affect a time taken to download updated dynamic data.

The input devices may define one or more sensing modes for detecting objects or contexts such as road markings, road signs or traffic conditions, etc. The map data/dynamic data may define a further sensing mode for detecting at least some of the same objects or contexts.

Therefore, some objects and contexts can be determined from plural modes of information. The control system 200 may be configured to aggregate the multi-modal information and process the aggregated data to increase a confidence score of at least one property of the object or context. The property may relate to a presence or absence of the object or context, its location, its size, or anything else useful for autonomous mode driving. This advantageously enables a realistic indication of a driving context within at least the first sensing range. A required manoeuvre may only be performed if the confidence score is above a threshold.

A decision to perform a manoeuvre may be made on the basis of information from a longer-range low-trust sensing mode such as map data and/or dynamic data, but it may be required that the information leading to the decision is subsequently verified using a shorter-range high-trust sensing mode such as the sensing means, for the manoeuvre to be performed. For example, information from the sensing means may be used to verify that information from the map data/dynamic data is accurate, before one or more planned manoeuvres are performed. The longer-range low-trust sensing mode may correspond to map data and/or dynamic data. The shorter-range high-trust sensing mode may correspond to one or more of the above-described sensing means.

Other dynamic data that may be obtainable by the control system 200, e.g. via the TCU, may include dynamic traffic data indicative of an emergency services vehicle location. The dynamic traffic data may indicate if an emergency services vehicle is approaching. This provides advance warning for the host vehicle 10 to manoeuvre out of a position in which it would obstruct the emergency services vehicle. The data may be received from client-server, V2V and/or V21 communication.

The host vehicle 10 may additionally comprise at least one human-machine interface (HMI) (not shown), facilitating access to one or more of the functions of the control system 200 described herein, and/or for presenting one or more outputs of the control system 200 described herein to the occupant (e.g. driver). The presentation may use visual means, audio means or any other appropriate means. User inputs to the HMI may be via touch, gesture or sound-based commands, or any other appropriate means. The HMI may comprise one or more of an output HMI, an input HMI, or an input-output HMI. Examples of output HMI in a vehicle include a centre console display, an instrument cluster display, audio speakers, a head-up display, a rear seat occupant display, a haptic feedback device, or the like. Examples of input HMI include touchscreens, manual actuators such as buttons and switchgear, and sensors for speech command recognition or non-touch gesture recognition. The input HMI may be close to a driver's seat. Advantageously, some input HMI may be located on the steering wheel.

A handover process may be implemented for initiating the autonomous mode, which will now be described. The control system 200 may be configured to receive at least one signal indicative of a suitability of initiation of the autonomous mode. The received signal may be indicative of a vehicle characteristic. The received signal may be indicative of a user characteristic. The received signal may be indicative of an environment characteristic. The received signal may be from the sensing means, or from another part of the control system 200 such as an algorithm that processes the map data and/or dynamic data.

The control system 200 may be configured to cause output of an availability signal indicative of an availability of the autonomous mode in dependence on the received signal, for example for presentation to the occupant via an HMI. If no availability signal is output, the host vehicle 10 is not operable to enter the autonomous mode. The control system 200 may be configured to determine whether to transmit the availability signal in dependence on at least one of the vehicle characteristic, the user characteristic, or the environment characteristic. One or more criteria associated with one or more of the characteristics may need to be satisfied, for the availability signal to be transmitted. An indication of the availability signal may be continuously presented to the occupant until at least one of the criteria is no longer satisfied. The availability signal may be continuously presented to the occupant until a user input is received in response to the availability signal. Examples of the user input and examples of the criteria are defined below.

The control system 200 may be configured to receive the user input in the form of a user activation signal indicative of the occupant's request to initiate the autonomous mode in response to the availability signal. The user input may be made via HMI. The user activation signal may be received during driving of the host vehicle 10, in other words while the host vehicle 10 is in a travelable state. For example, the host vehicle 10 may be in the non-autonomous mode. The control system 200 may be configured to output a driving mode signal to cause the host vehicle 10 to initiate the autonomous mode in response to the user activation signal. Initiating the autonomous mode may comprise a transition phase during which control of vehicle movement is transitioned away from the occupant to the control system 200. A duration of the transition phase may be dependent on one or more of the vehicle characteristic, the user characteristic or the environment characteristic to ensure a smooth transition.

The environment characteristic may be indicative of an environment external to the host vehicle 10 and in the vicinity of the host vehicle 10. The environment may be a driving environment. The driving environment may be a current driving environment while the host vehicle 10 is being driven. The driving environment may be indicative of a type of road on which the host vehicle 10 is driving. Optionally, the control system 200 may be configured not to transmit the availability signal unless at least the environment characteristic satisfies a road type criterion. The environment characteristic may be indicative of other environments too.

The road type criterion may be satisfied if the environment characteristic is indicative that the host vehicle 10 is travelling on a required type of road. The required type may be a motorway. Articles 10) and 25 of the Vienna convention on road traffic define the term motorway. A motorway may be referred to as a freeway or highway in some countries. The term 'highway' is used in this document. For those countries which have not ratified the above convention, their highways are defined herein as those which possess many or all of the following characteristics of a highway: - Use of the road is prohibited to pedestrians, animals, cycles, mopeds unless they are treated as motor cycles, and all vehicles other than motor vehicles and their trailers, and to motor vehicles or motor-vehicle trailers which are incapable, by virtue of their design, of attaining on a flat road a speed specified by domestic legislation. This indication may be provided by a road sign; - Drivers are forbidden to have their vehicles standing or parked elsewhere than at marked parking sites; if a vehicle is compelled to stop, its driver shall endeavour to move it off the carriageway and also off the flush verge and, if he is unable to do so, immediately signal the presence of the vehicle at a distance so as to warn approaching drivers in time; - Drivers are forbidden to make U-turns, to travel in reverse, and to drive on to the central dividing strip, including the crossovers linking the two carriageways; - Drivers emerging on to a motorway shall give way to vehicles travelling on it; - The road is specially signposted as a motorway; - The road does not cross at level with any road, railway or tramway track, or footpath; - The road does not serve properties bordering on it; -The road is provided, except at special points or temporarily, with separate carriageways for the two directions of traffic, separated from each other either by a dividing strip not intended for traffic.

The road type criterion may not be satisfied if the road is of another type and/or does not possess all or at least certain ones of the above characteristics. For example, some roads are main roads that possess many of the above characteristics but allow pedestrians and non-motorized vehicles to use the roads. The availability signal may not be transmitted for such roads.

In other examples, the required type of road may be another type of road rather than a highway, or the requirement may merely be that the host vehicle 10 is not on a certain type of road such as a minor or urban road. Optionally, the road may be required to possess multiple lanes in a direction of travel of the host vehicle 10 to satisfy the road type criterion.

In other examples, there may be no road type criterion for entering the autonomous mode.

The driving environment such as the type of road may be determined directly from metadata in the map data. The metadata may be indicative that the road is a highway. Alternatively, the required type may be determined indirectly from indications that the road possesses one or more of the above characteristics. Indications of the above characteristics may be determined by recognition of relevant road signs or road markings conveying these requirements, or by recognition of infrastructure such as a dividing strip. This may be detected by the sensing means and recognized by an object classification algorithm or determined from the map data or dynamic map data.

The environment characteristic may be indicative of a current weather condition in the vicinity of the host vehicle 10 or an upcoming weather condition to be encountered by the host vehicle 10. Information indicative of a weather condition may be indicative of rain falling on the host vehicle 10. The information may be indicative of the presence of snow or ice on the ground. The information may be indicative of at least one of a temperature, a humidity, a wind speed, a visibility, atmospheric pressure, precipitation. The control system 200 may be configured to not output the availability signal unless at least one weather criterion is satisfied. weather criterion may be satisfied if an indicated weather condition is a predetermined acceptable weather condition or is not a predetermined unacceptable weather condition. A weather criterion may be satisfied if an indicated temperature is within a predetermined acceptable temperature range. A weather criterion may be satisfied if an indicated humidity is within a predetermined acceptable humidity range. A weather criterion may be satisfied if an indicated atmospheric pressure is within a predetermined acceptable pressure range. The weather condition may be determined from a sensor on the host vehicle 10 or from information downloaded from an offboard weather service.

The user characteristic may be indicative of a current user characteristic of the occupant of the host vehicle 10 while the host vehicle 10 is being driven by the occupant. The user characteristic may be indicative of an awareness of the occupant of the vehicle. Information indicative of the awareness of the occupant may be obtained from one or more user sensors (not shown). The one or more user sensors may comprise at least one of a camera 308 and a physiological sensor to capture data indicative of the awareness of the occupant. The control system 200 may be configured not to output the availability signal unless at least one awareness criterion is satisfied. The occupant's awareness may need to be above a predetermined awareness threshold to satisfy the awareness criterion. In an implementation, the awareness may be quantified by numerical indicators such as a frequency or length of time for which the occupant's gaze has not been within a predefined area associated with driving, a blink rate, a head pose angle, or the like. In other words, the autonomous mode may be unavailable to the occupant of the host vehicle 10 if the occupant is not sufficiently aware to be able to resume control of the host vehicle 10 from the autonomous mode if required. In some examples, the occupant characteristic may relate to a physiological state. To satisfy a physiological criterion for the availability signal, quantifiable indicators such as heart rate or brain activity may be detected using one or more biometric sensors.

The user characteristic may be indicative of a separation of at least a part of the occupant from one or more controls of the host vehicle 10. For example, the user characteristic may be indicative of whether one or more hands of the occupant are on the steering wheel. The availability signal may be determined not to be output unless at least a non-separation criterion is satisfied. The non-separation criterion may be satisfied if one or more hands of the occupant are on the steering wheel.

The vehicle characteristic may be indicative of a current vehicle characteristic of the host vehicle 10 while the host vehicle 10 is being driven. The vehicle characteristic may be indicative of a current speed of the host vehicle 10. Information indicative of the current speed could be obtained from a speed sensor (not shown). The availability signal may be determined not to be output unless at least a speed criterion is satisfied. The speed criterion may be satisfied if an indicated current speed of the host vehicle 10 is within a predetermined acceptable speed range, such as less than an upper limit of about 130 kilometres per hour. Other vehicle characteristics may be checked too such that the availability signal is determined not to be output in one or more of the following situations: a tyre pressure is outside a predetermined acceptable range; an oil level is below a predetermined threshold; a fuel level is below a predetermined threshold; the host vehicle 10 is towing; a loaded weight of the host vehicle 10 exceeds a predetermined threshold; or a state of health of one or more components of the host vehicle 10, e.g. a traction battery, is outside a predetermined acceptable state of health.

The vehicle characteristic may be indicative of a detection range of one or more of the sensing means. The detection range may be less than the first sensing range in certain conditions, particularly weather conditions such as fog. The availability signal may be determined not to be output unless at least a detection range criterion is satisfied. The detection range criterion may be satisfied if the received signal is indicative that the detection range of the one or more sensing means is greater than a predetermined range threshold.

The autonomous mode may be unavailable to the occupant of the host vehicle 10 if the detection range of the one or more sensors does not meet the predetermined range threshold.

Once the transition phase is entered, control of the host vehicle 10 moves away from the occupant and to the control system 200 of the host vehicle 10. The transition phase may comprise modifying a vehicle movement in preparation for the end of the transition phase. For example, a steering of the host vehicle 10 may be controlled autonomously during the transition phase to substantially centre the host vehicle 10 within a lane of the road. A braking torque of the host vehicle 10 may be controlled autonomously during the transition phase to control a distance of the host vehicle 10 from a further vehicle ahead of the host vehicle 10 along a road. During the transition phase, the host vehicle 10 may also continue to respond to manual control inputs from the occupant. As the transition phase progresses, the host vehicle 10 may become less responsive to user control until the host vehicle 10 is controlled fully autonomously in the autonomous mode. The occupant is informed of progress through the transition phase by the transition signal described hereinbefore.

Once the transition phase is complete, the control system 200 controls the host vehicle 10 in the autonomous mode. SAE International's J3016 defines six levels of driving automation for on-road vehicles. The term autonomous mode as used herein will be understood to cover any of the SAE levels three or higher, such that the control system 200 will control all aspects of the dynamic driving task. At levels four or five, one or more aspects of one or more of the handover processes described herein for transitioning to and/or from the autonomous mode may not be implemented.

Driver-assistance functions such as cruise control, adaptive cruise control,a lane change assistance function, or a lane keeping function, are at a lower level of autonomy than the autonomous mode.

In the autonomous mode the occupant may not be required to keep one or more hands on the steering wheel, so a monitoring step requiring the occupant to keep one or more hands on the steering wheel may be omitted. In other implementations, the autonomous mode may require the monitoring step. Whether the hand(s) are on the steering wheel may be determined using any appropriate sensing means such as a touch sensor or camera or steering wheel torque/angle sensor. The monitoring may be performed periodically or continuously. If the hands are not on the steering wheel, one or more prompts may be issued.

The host vehicle 10 may comprise a driver distraction function. One or more distraction criteria associated with the driver distraction function may be inhibited upon entering the autonomous mode. For example, in the non-autonomous mode the driver distraction function may alert the occupant when their gaze points outside a predetermined area such as the windscreen. The alert may be transmitted when the gaze is outside the predetermined area for a threshold duration and/or frequency. In the autonomous mode the driver distraction function may be disabled or the predetermined thresholds may be modified to become more permissive.

While the host vehicle 10 is in the autonomous mode, one or more algorithms are implemented for controlling speed and/or direction of the host vehicle 10. The control system 200 transmits the output signals to the actuators in dependence on the algorithms. The algorithms may comprise at least some of: a lane centring algorithm; a lane change algorithm; a path planning algorithm; a speed control algorithm; a machine learning algorithm. The algorithms may be context-aware. The algorithms may process information from one or more of the sensing means: map data; dynamic data; and navigation constraints. For example, the algorithms may be traffic-aware from the dynamic traffic data.

The algorithms may interoperate with each other to determine the output signals. The algorithms may plan variations of the output signals over a future period of driving.

Algorithms for autonomous driving are known and include regression algorithms, classification algorithms, clustering, and decision matrix algorithms. Cost or loss functions may be employed to find optimal paths and speeds and minimize risk to humans.

The lane centring algorithm is for keeping the host vehicle 10 within a predetermined lateral position (target lane position) within lane lateral edges (lane boundaries). The lane boundaries may be identified by specific road markings under the relevant highway law. If road markings are not visible, for instance due to faded paint, a putative lane and/or its boundaries may be identified based on detection of a traffic corridor of other road users driving in a detected consistent manner, e.g. in lines.

The lane position may be off-centre on occasion, dependent on detected characteristics such as environment characteristics, e.g. other road users or infrastructure proximal to a lane boundary. This provides a reassuring separation between the host vehicle 10 and lateral objects. A minimum separation from one or both lane boundaries may be maintained.

The minimum separation may be around 0.3 to 0.6 metres from the nearside boundary, optionally 0.5 metres.

The lane change algorithm may be for keeping the host vehicle 10 within a nearside lane if required by applicable highway law. The lane change algorithm may enable the host vehicle to manoeuvre from a first lane to a second lane to avoid detected traffic. The lane change algorithm may enable the host vehicle 10 to implement a vehicle overtaking function to overtake another road user. The lane change algorithm may enable the host vehicle 10 to change lanes to follow a navigation route. A turn signal/indicator of the host vehicle 10 may be flashed automatically just before the lane change is performed.

Keeping the host vehicle 10 within a nearside lane may be the responsibility of a nearside bias function of the lane change algorithm. The nearside bias function may require a nearside lane to be selected in normal driving conditions. The nearside bias function may comprise one or more parameters that define constraints to be met. The constraints may be for lane hogging avoidance. An example constraint may be to delay changing lane from a nearside lane to an offside lane to overtake other road users until the overtake can be performed within a threshold time. A related constraint may be to change lane from the offside lane back to the nearside lane following an overtake as soon as possible. The threshold time may be the time spent outside the nearside lane without overtaking another road user in the nearside lane. The threshold may depend on applicable highway law but tends to be of the order of tens of seconds rather than minutes.

Whether a lane change is performed may depend on a space availability signal indicative of a presence of a space in front of or behind another road user of a size sufficient to accommodate the host vehicle 10, should the host vehicle 10 need to change lanes to occupy that space. The space availability signal may be determined in dependence on inputs from the sensing means. The space availability signal may affect where, when and/or how fast a manoeuvre is performed. For example, the space availability signal may be used by the speed control algorithm when the lane change algorithm determines a requirement for a lane change. The space may be in a target lane for the lane change. The space may be between a lead (downstream) other road user and a rear (upstream) other road user. The space may be a current or expected space. The control system 200 may be configured to determine if the expected space will have a size sufficient to accommodate the host vehicle at a predetermined time in the future. Determination of the expected space may depend on a detected indication of a relative speed of the other road user or users. The speed may be controlled in dependence on the space availability signal, for example to ensure that the space in front of and behind the host vehicle 10 is of a sufficient, e.g. above-threshold, detected size. The threshold size is an example of a manoeuvring constraint to be satisfied before the manoeuvre can be performed. The threshold may depend on the speed of the host vehicle 10. The speed of the host vehicle 10 may be controlled before the lane change. The speed may be controlled to be close to a speed of a lead other road user, a speed of a rear other road user, or between both.

The path planning algorithm may be for planning a specific path to be followed. Planning the path comprises determining one or more manoeuvre requirements indicative of required manoeuvres of the host vehicle 10. A manoeuvre is defined herein as a change of speed or course. Changing course may be performed using the steering control actuator.

Absent of navigation constraints, the path may follow the highway as far as possible. With navigation constraints, the path may follow those portions of the navigation route during which the autonomous mode is on or available. The path may extend beyond the first sensing range. The portion of the path within the first sensing range may be optimised.

Examples of optimisations include reducing/minimizing targets such as derivatives of velocity (acceleration, jerk) when steering the host vehicle 10. Cost functions or the like may be used to perform optimisations.

The speed control algorithm is for planning a required speed of the host vehicle 10 to be followed using the torque control actuators. The speed control algorithm may enable functions such as adaptive cruise control, overtaking speed boost, and lane changes. The speed control algorithm may also be for complying with a speed limit detected using road sign recognition or map data. The speed may be controlled in advance of traffic conditions beyond the first sensing range, indicated for example by the dynamic data. The speed control algorithm may determine a speed to maintain a required separation from a lead object and/or rear road user, i.e. a required headway, in accordance with adaptive cruise control methodologies.

The machine learning algorithm is for controlling one or more parameters of one or more of the other algorithms, in dependence on information indicative of past use of the host vehicle 10. The information may be indicative of past use of the host vehicle 10 in the autonomous mode and/or the non-autonomous mode. The information may be indicative of inputs such as steering inputs, acceleration inputs and braking inputs. The information may be indicative of environment characteristics. The information may be associated with information from the sensing means. The information may be associated with traffic conditions, road works or the like. The information may be indicative of locations of the past use. The information may be indicative of a temporal pattern of use of the host vehicle 10. For example, the times of the past use may have been recorded. The temporal pattern may enable locations visited at a recurring time and/or day and/or date to be established, such as a workplace. The information may be used for training of the machine learning algorithm. Machine learning enables an optimization of vehicle behavior for repeated journeys. Further, at least some of the parameters may be user-settable using HMI according to preference.

Whether a manoeuvre is performed may be subject to one or more manoeuvring constraints.

If a manoeuvring constraint cannot be satisfied, the path planning algorithm may need to modify the manoeuvre or an abort condition for aborting the manoeuvre may even be satisfied. In an example, the abort condition may be satisfied when the cost of performing the manoeuvre is high. The abort condition may be satisfied when the cost of performing the manoeuvre is higher or a threshold amount higher than the cost of performing a different manoeuvre. If an abort condition is satisfied, the manoeuvre is not performed. The abort conditions may be checked just before performing the manoeuvre. An example check for satisfaction of the abort condition comprises continually detecting objects as described above. An object may render an intended manoeuvre or already planned path inappropriate.

A static object obstructing the path may be such an object. Examples include roadworks or debris intersecting the path. Another road user, whether moving or not, may also render the manoeuvre or path inappropriate. The check may be dependent on an expected trajectory of the other road user relative to the planned path of the host vehicle 10. If the other road user is predicted to need to change its speed and/or course as a result of the manoeuvre by the host vehicle 10, the abort condition may be satisfied. The check may depend on detection of signals of intent from the other road users such as turn signals. If an abort condition is satisfied, the host vehicle 10 may remain in the autonomous mode and the speed and/or path may be re-planned accordingly.

In certain circumstances, the autonomous mode may need to hand control at least partially back to the occupant by switching to the non-autonomous mode. The non-autonomous mode may be entirely non-autonomous or may be less autonomous than the autonomous mode. The non-autonomous mode may require manual control or at least supervision by a human driver. The non-autonomous mode may comprise one or more driver assistance functions. For example, the non-autonomous mode may comprise at least one of the following functions: cruise control; adaptive cruise control; lane keeping assistance; braking assistance; overtaking assistance; parking assistance.

The control system 200 may be configured to receive at least one further signal indicative of a requirement to switch from the autonomous mode to the non-autonomous mode. The further signal may be indicative of a vehicle characteristic. The further signal may be indicative of a user characteristic. The further signal may be indicative of an environment characteristic. The further signal may be from the sensing means, or from another part of the control system 200 such as an algorithm that processes the map data and/or dynamic data.

The control system 200 may be configured to cause output of a user prompt signal in dependence on the further signal, for example if it is determined that a required highway exit junction approached by the host vehicle 10 is within a threshold driving time and/or distance.

The user prompt signal may prompt the occupant to take an action to enable the host vehicle 10 to transition out of the autonomous mode. If the occupant takes the prompted action, the host vehicle 10 transitions out of the autonomous mode. If the occupant does not take the prompted action, the occupant may be determined to be non-responsive which is an internal hazard associated with the host vehicle 10, therefore the control system 200 may determine a requirement to stop the host vehicle 10 and cause the host vehicle 10 to stop accordingly. In some examples, the requirement to stop may be determined before the user prompt signal is output, for example in dependence on a vehicle characteristic, user characteristic and/or environment characteristic. For example, a failure of a vehicle component may have occurred or the occupant may be unconscious.

The user prompt signal may be presented to the occupant via HMI. The control system 200 may be configured to receive a user readiness signal from the occupant in response to the user prompt signal. The user readiness signal may be transmitted in dependence on user actuation of HMI or a vehicle control such as the steering wheel. In one example, the HMI comprises a plurality of input HMIs on the steering wheel. The input HMI may comprise buttons or any other appropriate means. The input HMIs may be located at left and right sides of the steering wheel with reference to a centred steering wheel, i.e. no steering lock applied. The input HMIs may be located such that at least one digit of each the occupant's hands can remain at least partially hooked over the circumferential tube-like member of the steering wheel, at 9 o'clock and 3 o'clock or 10 o'clock and 2 o'clock positions, when the input HMIs are actuated by the occupant's hands. The input HMIs may need to be pressed concurrently and/or for a threshold duration.

Additionally or alternatively, the user readiness signal may be transmitted in dependence on user actuation of a vehicle control such as the steering wheel, accelerator pedal or brake pedal. For example, turning the steering wheel or depressing the pedal by more than a threshold amount causes the user readiness signal to be transmitted. In other examples, the HMI could take any other appropriate form.

The control system 200 may be configured to determine whether a user readiness signal has been received within a predetermined period of time from the user prompt signal. For example, the predetermined period of time may be from the range approximately 10 seconds to several minutes, depending on the required trade-off between user reaction time and maximum autonomous mode driving time. If the autonomous mode is for highway driving only, the predetermined period of time may be longer, in the order of minutes rather than seconds. For example, the predetermined period of time may be two or more minutes. The predetermined period of time may depend on the level of autonomy of the host vehicle 10, and may be greater for level four than for level three. The predetermined period of time may vary in use in dependence upon the vehicle characteristic, the user characteristic and/or the environment characteristic. The predetermined period of time may be settable by the occupant although may not be below a minimum time. The control system 200 may be configured to output one or more reminder signals for presentation to the occupant via HMI, between transmitting the user prompt signal and receiving the user readiness signal. For example, the reminder signal may comprise at least one of an audible alert, a haptic alert, a visual alert. A characteristic of the reminder signals such as a frequency, volume, number of output HMIs employed, may vary for each subsequent reminder signal. In an implementation, the user prompt signal at 0 seconds causes an audible instruction, a first reminder signal at 20 seconds causes another audible instruction, and subsequent reminder signals at 30, 40, 50 seconds etc., each cause a combination of an audible instruction, and haptic pulses through the driver's seat and/or steering wheel.

The environment characteristic, vehicle characteristic and/or user characteristic may be as described above, wherein the user prompt signal is transmitted if one or more of the criteria described above are no longer satisfied. Additionally or alternatively, different environment characteristics, vehicle characteristics and/or user characteristics may be defined for the determination whether to transmit the user prompt signal.

Regarding the environment characteristic, the control system 200 may be configured to transmit the user prompt signal in response to a current or upcoming change of driving environment. The upcoming change may be within a threshold distance or driving time. The change may be caused by non-satisfaction of the road type criterion and/or weather criterion as described above. Additionally or alternatively the change may be caused by detection of one or more of: a traffic light on the road; a toll booth on the road; an off-ramp from the road for following a navigation route. The off-ramp may specifically be for leaving a highway onto a minor road, rather than for transitioning from one highway to another highway.

Regarding the user characteristic, the control system 200 may be configured to transmit the user prompt signal in response to a changed user characteristic. For example, the change may be caused by non-satisfaction of the awareness criterion and/or the physiological criterion. In an implementation, the user prompt signal may be transmitted if the occupant is drowsy or unconscious.

Regarding the vehicle characteristic, the control system 200 may be configured to transmit the user prompt signal in response to a changed vehicle characteristic. For example, the change may be caused by non-satisfaction of the detection range criterion or any other of the criterion or situations described earlier. Additionally or alternatively, the change may be caused by a determination of a fault with the host vehicle 10, which is defined as a type of internal hazard associated with the host vehicle 10. The fault may be caused by one or more of: power failure; communication failure; or sensing means failure. The power failure may comprise an electrical power failure such as a failure of the power supply and/or backup power supply. The power failure may comprise a mechanical power failure such as an inhibited availability of propulsive torque from the prime mover, which may be caused by the prime mover becoming inoperable or entering a limp home mode. The mechanical power failure may correspond to a failure of a drivetrain component such as the transmission or differential. The mechanical power failure may correspond to a failure of an actuator with a responsibility for the dynamic driving task in autonomous mode. The power failure may comprise failure of headlamps at night. The communication failure may comprise a failure of one or more of the electronic communication networks. The communication failure may comprise a failure of one or more controllers with a responsibility for the dynamic driving task in autonomous mode. The communication failure may comprise a failure of a domain controller. The sensing means failure may comprise a failure of one or more of the sensing means. The fault may trigger a determination that the host vehicle 10 is to stop. The user prompt signal may be transmitted to enable the occupant to control how the host vehicle 10 is stopped. The control system 200 may be configured to stop the host vehicle 10 without driver intervention.

Various methods will now be described for being performed during autonomous driving in the autonomous mode. At least some of the methods are in accordance with one or more aspects of the present invention. The control system 200 could be configured to implement one or more of the methods. Computer software could be configured to, when executed, perform one or more of the methods via the control system 200.

With reference to Figs 3 to 4, there is provided a method 3000, 3100 for controlling the host vehicle 10 operable in the autonomous mode (and, in some examples, operable in the non-autonomous mode), the method comprising: causing 3002, 3106 the host vehicle 10 to enter the autonomous mode in response to a user activation signal during driving of the host vehicle 10; and in dependence on the user activation signal, causing 3004, 3110 a request for user navigation input from an occupant of the host vehicle 10.

By way of context, in the autonomous mode the occupant may not be required to keep one or more hands on the steering wheel as mentioned earlier. Further, driver distraction function criteria may be inhibited. Therefore, requesting the user navigation input after the user activation signal, rather than before the user activation signal, advantageously enables the occupant to take their hands off the steering wheel and/or look away from the windscreen to make the requested user navigation input, if permitted by the autonomous mode.

Fig 3 illustrates the example method 3000. At block 3002, the method comprises causing the host vehicle 10 to enter the autonomous mode in response to a user activation signal during driving of the host vehicle 10. The user activation signal may be as described earlier. The user activation signal may have been received in response to the availability signal as described earlier. Causing the host vehicle 10 to enter the autonomous mode may comprise implementing the transition phase as described earlier. Once the transition phase is complete, the control system 200 controls the host vehicle 10 in the autonomous mode.

At block 3004, the method comprises causing a request for user navigation input from an occupant of the host vehicle 10, in dependence on the user activation signal. The occupant may be the driver. The request for user navigation input may be performed once the host vehicle 10 has entered the autonomous mode, for example the request may be output once the transition phase is complete.

Accepted user navigation inputs may comprise navigation constraints. For example, the requested user navigation input may comprise a location. The location may comprise at least one of: a destination; or a waypoint.

In some examples, the location may comprise a location associated with transitioning from the autonomous mode to the non-autonomous mode. The location associated with transitioning from the autonomous mode to the non-autonomous mode may be a location at which the above-described further signal indicative of a requirement to switch from the autonomous mode to the non-autonomous mode is expected to be received. For example, the location associated with transitioning from the autonomous mode to the non-autonomous mode may be indicative of a change of driving environment. The change of driving environment may comprise a change from a highway to another category of road. The change of driving environment may comprise a junction. The junction may comprise an off-ramp to be used for following a navigation route. This may be advantageous if the autonomous mode is not available for a whole journey, for example if it is only available for the highway portions of a journey.

In some examples, the requested user navigation input may comprise a navigation route.

For example, the route may comprise a route to avoid. The route may comprise a route to select from a plurality of available routes for reaching a location.

The request may take the form of an HMI prompt. For example, the request may be presented on a display that is normally used by the navigation subsystem, such as the centre console display or instrument cluster display. The request may be presented subtly such that existing functions displayed on the display are not concealed. For example, if the request is displayed proximal to an area of the display presenting a function such as a map, the request presentation may not overlie the area or may be at least translucent. The area may be resized to accommodate the request. This means that if the occupant is reliant on the function such as the map and does not wish to make a user navigation input, the request is less likely to impair the occupant's use of the function and therefore distract them.

A user navigation input made in response to the request may comprise a confirmation response that a specific user navigation input will be made, for example a one-touch press of a touchscreen user interface element or a voice command. This may update an HMI to a state for receiving the specific user navigation input. For example, a navigation interface may then be presented.

Alternatively, the request itself may comprise the navigation interface, so the occupant can make a specific user navigation input immediately. In this example, the specific user navigation input is the confirmation response.

The navigation interface may enable a location to be entered. The navigation interface may enable locations to be searched using one or more keywords. The navigation input may be configured to receive a user navigation input that specifies the relevant location, route, etc. The request may time out if no user navigation input is received within a predetermined time.

The predetermined time may be in the order of seconds or minutes. A user navigation input before the timeout may require fewer user inputs and/or simpler user inputs and/or provides a larger area of an input device, e.g. touchscreen, in which to make user inputs, compared to the situation in which a user navigation input is made after the time out.

If the request times out, an alert may be transmitted to the occupant via HMI, e.g. alerting them that the host vehicle 10 in the autonomous mode will stay on a current road unless or until a user navigation input is received.

If the further signal indicative of a requirement to switch from the autonomous mode to the non-autonomous mode is received, the request may be removed from the HMI in dependence thereon.

The method may make suggestions to assist with making a user navigation input. The method may comprise processing information indicative of a pattern of use of the host vehicle 10. The information may be from the machine learning algorithm as described earlier. The pattern of use may comprise a single past journey of the host vehicle 10 or a plurality of past journeys of the host vehicle 10.

The method may suggest one or more locations and/or routes.

At least one of the suggestions may be dependent on processing information indicative of a user schedule.

Information indicative of a user schedule may comprise, for example, calendar information. The calendar information may comprise events. The events may comprise metadata such as location metadata. Location metadata may include a direct location reference such as a geographical address, or a location may be inferred from other metadata. For example, if an event is marked as 'holiday' or 'work from home', suggestion of a workplace location may be inhibited.

The information indicative of a user schedule may have been input into the host vehicle's infotainment system. In some examples, the host vehicle 10 may obtain the information from a user electronic device via a connection of the host vehicle 10 to the user electronic device.

The user electronic device may be a mobile phone or the like. In some examples, the host vehicle 10 may obtain the information from an off-board service (e.g. calendar app) subscribed to by the user, via telematics.

At least one of the suggestions may be dependent on processing information indicative of a pattern of use of the host vehicle.

The temporal information indicative of a temporal pattern of use of the host vehicle 10 may be used. The suggested one or more locations may comprise a location toward which the host vehicle 10 is travelling. The locations may be ones which the host vehicle 10 has been to before. The suggested one or more locations may comprise a location visited at a recurring time and/or day and/or date. The suggested one or more routes may comprise a route towards or along which the host vehicle 10 is travelling, and/or has travelled before.

In an example, the method may comprise determining that the host vehicle 10 has travelled from point A to point B and is now travelling back from point B to point A. This may be indicated by the direction and/or route of the current journey compared to the direction and/or route of the last journey, or the last journey(s) starting from point A. In some examples, point A may be a default location, marked in the map data by metadata such as 'home'.

The suggestion may be influenced by a machine learning tool such as probabilistic forecasting. Different locations may be assigned different probabilities. The probability is a probability that the host vehicle 10 is heading towards that location. The probability may be determined by one or more parameters such as whether the host vehicle 10 is travelling towards or away from a location (i.e. direction); a route followed by the host vehicle 10; the time; the day; the date; or who is detected to be driving the host vehicle 10. Each parameter may define a probability score for each location based on the pattern of past use of the host vehicle 10. The location with the highest combined probability score may become a suggested location. For example, if the current day is a weekday, the time is before 9am, and the host vehicle 10 is heading towards a location most frequently travelled to on weekdays before 9am, that location may be suggested. The location may likely be a workplace. The location with the highest probability may be the only suggested location or may be more prominently presented than other locations. The probability scores may be weighted, for example based on age. Older information may comprise a lower weighting so that the host vehicle 10 will adapt to changes such as moving house or workplace.

At least one of the suggestions may be dependent on processing information pushed from a third-party service. The third-party service may comprise an advertising service, an events service, or a combination thereof. Therefore, the user may be presented with suggestions to travel to relevant events or venues.

The user navigation input may take the form of the confirmation response confirming at least one suggested location/route.

An option to manually enter a location/route may be presented alongside the one or more suggestions or if no confirmation is received, in case the suggestion(s) do not correspond to the user's intentions.

Fig 4 illustrates a method 3100. Block 3106 is the same as block 3002. Block 3110 is the same as block 3004. The method 3100 defines an example detailed implementation of the method 3000. The method 3100 also optionally comprises an additional function of optimising a download of dynamic data, at block 3120.

Upon entering the autonomous mode at block 3106, block 3108 comprises determining whether navigation constraints have already been determined for a current journey of the host vehicle 10. The navigation constraints may comprise a navigation route. The navigation constraints may be in response to an earlier user navigation input.

Determining whether navigation constraints are already in use may comprise determining whether the host vehicle 10 is actually obeying the navigation constraints. For example, if the host vehicle 10 is off-course the occupant may have decided not to follow the navigation route.

Block 3108 may be performed before or after block 3106.

The determination of block 3108 may be positive ('Y' in Fig 4) if navigation constraints are currently set in the navigation subsystem. In some examples, it may further be required that the navigation constraint is actually being obeyed as mentioned above. If the determination is positive, the existing navigation constraints are used for the autonomous mode, at block 3112. If the determination is negative, the method progresses to block 3110 to request the user navigation input. The request may be in the manner described above.

At block 3114, it is determined whether the user navigation input has been received in response to block 3110. The determination may be positive if a sufficient user navigation input has been received to enable a new navigation constraint to be defined, such as a navigation route. In response to a positive determination, the method proceeds to block 3116 in which new navigation constraints, defined in dependence on the user navigation inputs, are used for the autonomous mode. In response to a negative determination, the method proceeds to block 3118 in which the autonomous mode causes the host vehicle 10 to remain on a highway on which the host vehicle 10 is currently driving until handover to the non-autonomous mode. This may be accompanied by an alert as described above.

The method 3100 optionally comprises block 3120, which comprises optimising a download process. This is described below.

With reference to Figs 4-5, there is provided a method 3500. The method 3500 may be an example sub-routine for performing block 3120 of Fig 4 or may be independent from the methods of Figs 3 and 4. The method comprises processing 3502 information indicative of a pattern of use of the host vehicle 10; and causing 3504 downloading of dynamic map data and/or dynamic traffic data from a remote information source 302 in dependence on the processing.

By way of context, at least some dynamic data may need to be updated (downloaded) sufficiently frequently that it is unlikely that the download can always be performed while the host vehicle 10 is parked using a short-range communication network. Therefore, at least some downloads may need to be performed while the host vehicle 10 is in a travelable state.

The download may be performed while the host vehicle 10 is being driven in the autonomous mode and/or the non-autonomous mode. The download may be at least partially over a cellular network.

Unfortunately, cellular networks have locations and/or times of inhibited connectivity. Service blind spots may occur in locations such as tunnels or mountainous regions. Quality of service can also drop at peak times. The host vehicle 10 may have limited opportunities to perform the download. In extreme cases, a very high proportion of the host vehicle's service life will be spent driving through blind spots of cellular coverage. Without frequent downloads, some autonomous mode features may become unreliable, such as the algorithms described earlier that utilise dynamic data (e.g. lane centring algorithm, nearside bias function, path planning algorithm, etc). If the download were attempted at predetermined times, it would be unlikely that any predetermined time would correspond with a time when the host vehicle 10 has a good likelihood of success of completing the download. Therefore, by performing the download in dependence on the pattern of past use of the host vehicle 10, the chance of success of the download is improved.

At block 3502, the method 3500 comprises processing information indicative of a pattern of use of the host vehicle 10. At least some of the information may be as described earlier, for example in connection with the machine learning algorithm and/or block 3004 of Fig 3.

The information indicative of a pattern of use of the host vehicle 10 may comprise driving information associated with past driving of the host vehicle 10. Relevant driving information includes at least one of: past routes of the host vehicle 10; past locations at which the host vehicle 10 has previously been; past speeds of the host vehicle 10; the temporal pattern of use of the host vehicle 10; or the like. Example locations may comprise individual map positions, areas such as cells or communities, or sections of roads. Example temporal pattern information may record the times of past use of the host vehicle 10. The temporal pattern information may bin the times into distinct time bins (intervals).

The information may be indicative of a pattern of use of the host vehicle 10 associated with other tasks, such as downloading the dynamic data. The information may comprise download information indicative of one or more past download attempts. The past download attempts may comprise attempts to download/update the dynamic data. In some examples, the past download attempts may comprise downloads/updates of other software components, to expand the available training dataset. In some examples, the past download attempts may comprise test downloads of arbitrary payloads, to expand the available training dataset.

Block 3502 may comprise a training phase. Block 3502 may comprise a task phase. Block 3502 may comprise both a training phase and a task phase.

The training phase may produce and/or update a set of training data. The training phase may correlate download information with driving information. The training phase gathers useful download success/failure statistics which enables the task phase to be performed more accurately, and efficiently due to fewer attempts.

For example, as new/updated download information is received, it may be binned into a location bin (position, area or route section) associated with the download information to update the training data. Additionally or alternatively, the download information may be binned into a time interval bin associated with the download information to update the training data. The training phase may be performed on an ongoing basis during the service life of the host vehicle 10. The training phase may be performed on-board the host vehicle 10, or off-board in a cloud system, another vehicle, or any other server. Off-board training data may be acquired by the host vehicle 10 via V2V or V21 communication.

In an example implementation, the download information may indicate a time and/or a location at which a condition associated with downloading the dynamic data is not satisfied.

The condition may be associated with one or more characteristics of the past download(s).

Example characteristics may include one or more of: availability of cellular network coverage at the particular time or location; an indication of one or more past successful downloads at the particular time or location; or a characteristic indicative of a time taken to perform the download, at the particular time or location. The characteristics are therefore indicative of a quality of service.

A characteristic indicative of one or more past successful downloads may comprise an indication of whether a download completes successfully. A characteristic indicative of a time taken to perform the download may comprise an indication of a rate of data transfer, a cumulative time taken of the download, a number of retries of the download, or a combination thereof. A characteristic indicative of availability of cellular network coverage may comprise an indication of a number of users of a cell associated with the download (cell traffic), a signal strength of a connection to the cell, an error rate, or a combination thereof.

The cell may be a current cell and/or one or more expected cells along a navigation route of the host vehicle 10.

For example, the condition may not be satisfied if the download fails to complete successfully; if a rate of data transfer is below a threshold; if an error rate is above a threshold; if a number of users of a cell associated with the download is too high; if a number of retries of the download exceeds a threshold; if the time taken to perform the download exceeds a threshold; or a combination thereof.

The download information may be associated with the host vehicle 10 and/or with another vehicle which downloaded dynamic data. The use of information from other vehicles enables sharing of download statistics (training data of other vehicles), to provide better training data.

During the training phase, certain times and/or locations may be associated with frequent non-satisfaction of the condition. The association may be defined as an above threshold number of non-satisfactions of the condition for that time/location. The threshold may be absolute or relative to other times/locations. In an example, the association may be defined as a higher relative number of non-satisfactions of the condition compared to other times/locations. The download should not be attempted in such locations and/or at such times. A relative threshold beneficially provides a degree of optimization, if the download has to be performed within a set time.

Additionally or alternatively, the correlation may comprise determining a time and/or a location at which the condition is satisfied. The association may be defined as a below-threshold number of non-satisfactions of the condition for that time/location. The download should be attempted at these times/locations.

The task phase may comprise applying at least the training data to a download scheduling process, such that the dynamic data download is scheduled in dependence on the prediction phase.

In some, but not necessarily all examples, the task phase may comprise applying both real-time information and the training data to the download scheduling process. Real-time information may be associated with current or expected values of the training data, such as the cell traffic. The real-time information may be obtained by the host vehicle 10 from a third party by V2V or V21 communication.

The download scheduling may be performed on-board of off-board the host vehicle 10 similarly to the training phase, depending on whether the download is performed using a push or a pull approach. There are various ways in which the training data could be applied to a download scheduling process, discussed below.

In an implementation, the training data may control when/where the host vehicle 10 is in a first mode which permits downloads. The information may control when/where the host vehicle 10 is in a second mode which inhibits downloads. In one example, in the second mode a download may continue, be paused or cancelled if it is underway, but cannot commence if it is not already underway. A download may commence or un-pause when entering the first mode.

If the download is performed according to a push approach, push messages from the external information source may be rejected or ignored when/where the second mode is active. Push messages may be accepted when/where the first mode is active.

If the download is performed according to a pull approach, no pull messages may be sent to the external information source when/where the second mode is active. Pull messages may be sent when/where the first mode is active.

In an example implementation, the training data may be used to assign triggers for transitioning between the first mode and the second mode.

The trigger may comprise a location. For example, the training data and/or the real-time information may indicate that the condition is not satisfied or satisfied at specific known location(s). The known location is a download blind spot if the condition is not satisfied. The download blind spot may comprise an area or section of a road/route such as a tunnel or an area/cell associated with a low likelihood of download success, such as a high (above-threshold) demand area/cell.

The trigger for switching to the second mode may comprise a first location. The first location may be proximal to the known location such as proximal to an entry to the blind spot, for example the tunnel entrance.

The trigger for switching to the first mode may comprise a second location. The second location may be proximal to a known location such as proximal to an exit from the blind spot, for example the tunnel exit.

If only one of the first location or the second location corresponds to a known location from the training data, the other location may be a predetermined assumed distance from the known location.

The trigger may comprise a time. For example, the training data and/or the real-time information may indicate that the condition is not satisfied or satisfied at specific known times. For example, the network service is poor if the condition is not satisfied and good if the condition is satisfied. The network service may be poor between specific known times such as 6pm-10pm.

The trigger for switching to the second mode may be a first time. The first time may be proximal to the known time such as proximal to 6pm.

The trigger for switching to the first mode may be a second time. If the network service is good after 10pm, the second time may be proximal to the specific known time for good network service. If only one of the first time or the second time corresponds to a known time from the training data, the other time may be a fixed period from the known time.

The trigger may be dependent on both time and location. For example, the download may commence at a first location but not a second location if the host vehicle 10 is at the first location at a first time, but may not commence at the first location if the host vehicle 10 is at the first location at a second time. At the second time, a different location such as the second location may be more appropriate, or no location may be appropriate.

In some implementations, the scheduling of the download may be dependent on a specific journey. The journey may be a known journey or an expected journey. The journey may be a known journey if the occupant has already entered user navigation inputs to define a journey. The journey may be an expected journey when the navigation system has not yet received a user navigation input.

An expected journey may comprise an expected route, destination and/or timing of use of the host vehicle 10. The prediction could use the machine learning tool described above to predict the expected journey, for example. The training data may be interrogated for download information that applies to the expected journey. In an example, the location(s)/time(s) for the expected journey may correspond to some location(s)/time(s) for which download information is available. Then, a start time of the download may be scheduled for a specific location/time along the expected journey.

If the journey is a known journey, the process may be as described above except the prediction of the expected journey is not required.

If the journey is one that the occupant regularly makes, such as a commute, a large amount of download information may be available for that journey, so the method can be performed accurately. In an example, the temporal pattern information may indicate that the occupant completes a journey from location A to location B between the hours of 07:00 and 09:00 on weekdays, and a return journey from location B to location A between the hours of 17:00 and 19:00 on weekdays. Past download statistics indicate that condition is satisfied at a particular section of the route between locations A and B, or a return journey.

In some examples, the download schedule may be constrained by one or more scheduling constraints. An example scheduling constraint could implement a lower limit on update frequency, for example. The limit could be a time limit, a number of ignored push requests, a number of inhibited pull requests, or the like. The download schedule may need to operate within the scheduling constraints.

If the processing in block 3502 indicates that a scheduling constraint cannot be met, the download may be attempted immediately or scheduled for a time/location normally associated with the second mode just in case the download works. In some examples, if the scheduling constraint is not met, a notification may be provided to the occupant (via HMI for example) that the dynamic data may be out-of-date. The notification may recommend that the update may be performed by other means such as by connecting to a reliable network, e.g. wired connection or wireless local area network.

The dynamic traffic data download may differ from the dynamic map data download in various ways. The dynamic traffic data may be updated at a different rate from dynamic map data. For example, the dynamic traffic data may be updated more often than the dynamic map data.

In some examples, the update frequency of dynamic traffic data may be in the order of minutes. In some examples, the update frequency of the dynamic traffic data may be in the order of hours.

However, the update frequency of dynamic map data may be in the order of days. In other examples, the update frequency of the dynamic map data may be more regular (e.g. hours), or less regular (e.g. months).

In some examples, each dynamic traffic data download may have a different file size from each dynamic map data download. Optionally, the scheduling of the dynamic traffic data may therefore differ from the scheduling of the dynamic map data. The thresholds for satisfaction of the condition associated with downloading the dynamic data may differ. The trigger may differ. The scheduling constraints may differ. The planned start time/location of the download may differ.

At block 3504, the method comprises causing the download from the remote information source 302 in dependence on block 3502. For example, the download may commence upon occurrence of the required trigger.

A download may be scheduled predictively, for example the start time of the download may have been scheduled to start at a future time/location, based on when/where the host vehicle 10 is expected to be in the first mode. Alternatively, a download may be scheduled reactively, for example certain times/locations may be unavailable for download while the host vehicle 10 is in the second mode, without scheduling a particular download start time.

The manner of the download may be as described earlier in connection with the telematics control unit 304.

In the preceding examples the output signals (i.e. speed/direction of vehicle) of the autonomous mode are not controlled in dependence on block 3502. In other examples, the method may comprise controlling one or more of the output signals in the autonomous mode, in dependence on block 3502. For example, the host vehicle 10 may be slowed to allow more time to complete a download. The host vehicle 10 may follow or avoid a particular route in dependence on a likelihood of success of the download.

In the preceding examples, the download scheduling is dependent at least on information indicative of past use of the host vehicle 10 and/or indicative of downloads. Additionally, the download scheduling may be dependent on map data. The map data may indicate one or more locations associated with poor network coverage. For example, the map data may indicate the locations of tunnels. The map data may indicate the locations of valleys or mountainous areas.

The download scheduling may even be dependent on weather data indicative of weather proximal to the vehicle/route/location/time, as there is a correlation between SOTA download success and atmospheric conditions. Certain weather conditions may trigger the second mode.

Although the principles described above are for dynamic data for use in the autonomous mode, at least some of the principles are applicable to the download of other software components.

For purposes of this disclosure, it is to be understood that the controller(s) 202 described herein can each comprise a control unit or computational device having one or more electronic processors 204. A vehicle and/or a system thereof may comprise a single control unit or electronic controller or alternatively different functions of the controller(s) may be embodied in, or hosted in, different control units or controllers. A set of instructions 208 could be provided which, when executed, cause said controller(s) or control unit(s) to implement the control techniques described herein (including the described method(s)). The set of instructions may be embedded in one or more electronic processors, or alternatively, the set of instructions could be provided as software to be executed by one or more electronic processor(s). For example, a first controller may be implemented in software run on one or more electronic processors, and one or more other controllers may also be implemented in software run on or more electronic processors, optionally the same one or more processors as the first controller. It will be appreciated, however, that other arrangements are also useful, and therefore, the present disclosure is not intended to be limited to any particular arrangement. In any event, the set of instructions described above may be embedded in a computer-readable storage medium 210 (e.g., a non-transitory computer-readable storage medium) that may comprise any mechanism for storing information in a form readable by a machine or electronic processors/computational device, including, without limitation: a magnetic storage medium (e.g., floppy diskette); optical storage medium (e.g., CD-ROM); magneto optical storage medium; read only memory (ROM); random access memory (RAM); erasable programmable memory (e.g., EPROM ad EEPROM); flash memory; or electrical or other types of medium for storing such information/instructions.

The term 'if' is used herein in relation to the concept of conditional performance of a function 'if' a condition is satisfied. The term 'if' in this context means that the function is capable of being performed if the condition is satisfied and is not capable of being performed if the condition is not satisfied. Additional conditions (not stated) may also need to be satisfied before the function is performed. Therefore, although it may be that the stated condition is the only condition for performing some functions, the 'if' terminology herein does not limit to such scenarios.

Separation', 'distance' and 'position' as disclosed herein are not intended to be limited to absolute values of distance. The terms can be normalised by speed. For instance, a separation or distance may be two seconds (at 10 metres per second).

The blocks illustrated in the Figures may represent steps in a method and/or sections of code in the computer program 208. The illustration of a particular order to the blocks does not necessarily imply that there is a required or preferred order for the blocks and the order and arrangement of the block may be varied. Furthermore, it may be possible for some steps to be omitted.

Although embodiments of the present invention have been described in the preceding paragraphs with reference to various examples, it should be appreciated that modifications to the examples given can be made without departing from the scope of the invention as claimed. For the absence of doubt, the autonomous mode may be operable in non-highway roads.

Features described in the preceding description may be used in combinations other than the combinations explicitly described.

Although functions have been described with reference to certain features, those functions may be performable by other features whether described or not.

Although features have been described with reference to certain embodiments, those features may also be present in other embodiments whether described or not.

Whilst endeavoring in the foregoing specification to draw attention to those features of the invention believed to be of particular importance it should be understood that the Applicant claims protection in respect of any patentable feature or combination of features hereinbefore referred to and/or shown in the drawings whether or not particular emphasis has been placed thereon.

Claims

CLAIMS1. A control system for a host vehicle operable in an autonomous mode, the control system comprising one or more controllers, the control system configured to: process information indicative of a pattern of use of the host vehicle; and cause downloading of dynamic map data and/or dynamic traffic data from a remote information source in dependence on the processing.
2. The control system of claim 1, wherein the one or more controllers collectively comprise: at least one electronic processor having an electrical input for receiving the information; and at least one electronic memory device electrically coupled to the at least one electronic processor and having instructions stored therein; and wherein the at least one electronic processor is configured to access the at least one memory device and execute the instructions thereon so as to cause the host vehicle to perform the processing and the causing downloading.
3. The control system of claim 1 or 2, wherein the dynamic map data and/or dynamic traffic data download is scheduled in dependence on the processing.
4. The control system of claim 3, wherein the download schedule is a time and/or a location of the host vehicle, at which the download is to commence or not commence.
5. The control system of any preceding claim, configured to determine a time and/or a location, at which a condition associated with downloading dynamic map data and/or dynamic traffic data is satisfied or not satisfied.
6. The control system of claim 5, wherein the satisfaction or non-satisfaction of the condition at a particular time or location is determined in dependence on information indicative of at least one of: availability of network coverage at the particular time or location; an indication of one or more past successful downloads at the particular time or location; or a characteristic indicative of a time taken to perform the download, at the particular time or location.
7. The control system of claim 6, wherein the dynamic map data and/or dynamic traffic data download is scheduled to commence before a time or before the host vehicle reaches a location, associated with non-satisfaction of the condition, or wherein the downloading is scheduled to commence at a time or at a location of the host vehicle associated with satisfaction of the condition.
8. The control system of any preceding claim, wherein the dynamic map data and/or dynamic traffic data download is at least partially over a cellular network while the host vehicle is being driven.
9. The control system of any preceding claim, wherein at least one path planning algorithm of the host vehicle is configured to use the dynamic map data and/or dynamic traffic data when planning a path of the host vehicle during autonomous driving in the autonomous mode.
10. The control system of any preceding claim, wherein the information comprises an indication of a location at which the host vehicle has previously been and/or is indicative of a temporal pattern of use of the host vehicle.
11. The control system of claim 10, wherein the dynamic map data and/or dynamic traffic data download is scheduled to commence in dependence on an expected route and/or destination and/or timing of use of the host vehicle as determined by the processing of the information, without a navigation system of the host vehicle having received a user navigation input comprising a location and/or a route.
12. The control system of any preceding claim, wherein the dynamic map data and/or dynamic traffic data dynamically updates periodically, wherein the period is from the range of a plurality of minutes to one or more months.
13. The control system of any preceding claim, wherein the dynamic map data comprises information on at least one of: roadworks; lane closures; speed limit changes; weather conditions; road surface conditions, and/or the dynamic traffic data comprises information on at least one of: traffic conditions; an emergency vehicle location.
14. A method for controlling a host vehicle operable in an autonomous mode, the method comprising: processing information indicative of a pattern of use of the host vehicle; and causing downloading of dynamic map data and/or dynamic traffic data from a remote information source in dependence on the processing.
15. A vehicle comprising the control system of any of claims 1 to 13.
16. Computer software that, when executed, is arranged to perform a method according to claim 14.
17. A non-transitory, computer-readable storage medium storing instructions thereon that, when executed by one or more electronic processors, causes the one or more electronic processors to carry out the method of claim 14.