WO2008078088A1

WO2008078088A1 - Method of operating a vehicle

Info

Publication number: WO2008078088A1
Application number: PCT/GB2007/004931
Authority: WO
Inventors: Mark Richard Tucker; Martin John Thompson; Alastair James Buchanan
Original assignee: Trw Limited
Priority date: 2006-12-22
Filing date: 2007-12-21
Publication date: 2008-07-03
Also published as: GB0625726D0

Abstract

A method of operating a vehicle being driven along a road by a driver comprising, whilst the vehicle is being driven gathering data whilst the vehicle is being driven indicative of the manner in which the vehicle is being operated using a driver information device fitted to the vehicle, processing the data gathered by the device whilst the vehicle is being driven or afterwards or a combination of both to produce a signal representative of the manner in which the vehicle is being operated, the signal comprising at least one metric indicative of driver behaviour and/or congestion on the road at the time, and providing feedback to the driver indicative of the manner of operation, so as to modify the manner in which the driver operates the vehicle according to the at least one metric that is fed back to the driver. An on-board vehicle processing unit that provides feedback to a driver is also disclosed.

Description

METHOD OF OPERATING A VEHICLE.

This invention relates to a method of operating a vehicle and to a method and apparatus for improving driver behaviour.

It is widely recognised that poor driver behaviour can lead to accidents. It is also known that driver behaviour can influence the amount of emissions made by a vehicle. Many attempts have been made to improve driver behaviour through the use of traffic laws and forms of enforcement. Many roads have speed limits that are set by law according to the type of road and its location, and cameras are widely used to enforce these limits. The issue of fines as a form of feedback is widely believed to result in an improvement in driver behaviour. Keeping speeds down greatly improves safety and reduces emissions.

It is becoming recognised that efforts need to be made to reduce the damage that may be caused by vehicles to the environment in a more sophisticated way. This damage may be noise pollution due to the roar of an accelerating engine. It may be atmospheric pollution in the form of the emission of greenhouse gases. The applicant has also appreciated that a more sophisticated way of controlling congestion would also be desirable.

According to a first aspect the invention provides a method of operating a vehicle being driven along a road by a driver comprising: gathering data whilst the vehicle is being driven indicative of the manner in which the vehicle is being operated using a driver information device fitted to the vehicle; processing the data gathered by the device whilst the vehicle is being driven or afterwards or a combination of both to produce a signal representative of the manner in which the vehicle is being operated, the signal comprising at least one metric indicative of driver behaviour and/or congestion on the road at the time; and providing feedback to the driver indicative of the manner of operation, so as to modify the manner in which the driver operates the vehicle according to the at least one metric that is fed back to the driver.

The feedback of the metric or metrics may take the form of a report which may be issued to the driver in a printed or electronic form by post, fax, email, text (SMS or MMS) or any other way.

The method may comprise modifying the function of at least one system of a vehicle so as to directly or indirectly modify the manner in which the vehicle is functioning.

The modification of the vehicle function may be chosen to be a modification which provides feedback to the driver which may influence the driver's behaviour in a manner which tends to lead to a modification of the driver behaviour metric which in turn tends to optimise the operation of the vehicle.

By optimise we may mean achieving a reduction in emissions compared with a similar vehicle under identical operating conditions and driven historically in the same manner but which does not modify its function to influence the driver. It is not the change in function per se that provides the reduction in emissions, but the way the change causes the driver to modify his or her driving that does so. Of course, the change in function may also in its own right reduce emissions in some cases, particularly where the change relates to the engines function. This gives a double benefit. In an alternative, no modification of the vehicle function may be made and the improvement may be based solely on providing informative feedback on driver behaviour to the driver. As mentioned that may be in the form of a report. The common theme here is that feedback is again provided in some form. On receiving this feedback the driver may consider changing the way in which they drive. For instance it may make them less aggressive if it shows that they are accelerating and decelerating in a violent manner or making rapid direction changes or lane hopping.

The method may comprise giving feedback to the driver in the form of presenting the feedback on a display to the driver whilst they are driving. This may be substantially in real time or at a slight delay of perhaps a few seconds or fractions of a second.

The method may comprise modifying the manner in which the vehicle is driven by altering one or more characteristics of the vehicle. For example, it may comprise altering the fuel mixture fed to the engine of the vehicle, making it run more leanly to reduce emissions when the driver is exhibiting bad behaviour. It may comprise placing a limit on the available acceleration of the engine as a function of driver behaviour, e.g. worse behaviour the lower the available acceleration. This may also apply to a limit on the maximum available vehicle speed. Both of these could be achieved by modifying the control of the engine.

It may comprise altering the feel of a steering system fitted to the vehicle. It is known to the applicant that certain steering feel types can encourage a driver to steer more smoothly. This can be achieved by varying the "map" used to drive the steering motor in an electric power assisted steering system. The modification to the vehicle may be achieved automatically, by which we mean without driver intervention, and as a function of driver behaviour. The goal should be to encourage the driver to drive the vehicle in a manner which is less harmful to the environment or is safer for the driver and others around them.

In an extreme case, the method may comprise disabling the vehicle either completely or partially in the event that driver behaviour which is consistently bad for the environment is detected.

The steps of determining the driver behaviour signal and/or metrics may be performed remote from the vehicle or onboard. The method may therefore include steps of transmitting sensed or measured data to a remote device for processing.

According to a second aspect the invention provides an onboard vehicle processing unit for fitment to a vehicle comprising: data gathering means for gathering data representative of one or more operational parameters of the vehicle; processing means for processing the data to produce a driver behaviour signal defining at least one metric representative of the manner in which the driver is driving the vehicle; and feedback means for providing feedback to the driver dependent upon the driver behaviour signal.

The controller may further comprise modifying means adapted to modify one or more operational parameters of the vehicle as a function of the driver behaviour signal, the functions affecting the amount of impact the vehicle has on the environment so as to encourage good driver behaviour. The apparatus may optionally include a communication means for passing one or more of the gathered data and the driver behaviour signal to a remote receiver.

The device may include feedback means that provides feedback to the driver indicative of the at least one driver behaviour signal. The device may include one or more lights or a visual display on which this feedback is presented to the driver. For example, the device may include a set of red, amber and green lights, with the green only being indicated if the at least one signal indicates good behaviour and the red illuminated to indicate bad behaviour. Such as system is quickly and easily understood by most drivers.

Alternatively, or additionally, the feedback may comprise audible or haptic signals. The feedback may be achieved through modifying the operation of the vehicle. For example, any system in which a change can be detected by the driver could be modified. This includes the engine, steering, suspension etc. The changes are preferably any change which encourages better driver behaviour and which can be felt or otherwise detected by the driver, i.e. which give feedback. For example, the steering feel can be changed, or engine response or the suspension may be made softer. It is known that one or more such changes can alter the feel of the car encouraging a style of driving that is less harmful to the environment. For example, making the vehicle less responsive and less "sporty" can make the driver behave in a less aggressive manner. This change can be made dependent on the driving conditions such as the level of congestion or type of road or current driving style.

By making the vehicle respond to measured conditions and applying an appropriate change, subtle improvements in emissions can be made without detracting from the overall feel of the vehicle. The at least one driver behaviour signal may indicate whether the drivers behaviour is good or is bad or lies somewhere between the two.

It may comprise a metric representative of at least one (of many different) type of driver behaviour. It may represent a combined metric representative of a combination of two or more metrics. It may represent driver behaviour in terms of its effect on the environment. This may represent the amount of carbon dioxide that the driver is causing the vehicle to emit. Additionally or alternatively it may represent driver behaviour in terms of its effect on congestion. For example, the metric may give an overall rating in accordance with a traffic light scheme- red for worst and green for best, or a rating from 0 to 10 (best to worst or vice versa) . Such forms of reporting a considered high impact and easy to interpret at a glance.

The data gathering means for gathering data may comprise a range of different sensors or measuring systems that may be included as part of the device or even external to the vehicle. The sensors may be fitted within a common housing together with the rest of the device so that it is self contained. Alternatively, the data gathering means may merely comprise an input to which the required data is fed from remote sensors fitted elsewhere on the car.

The data gathering means may comprise one or more sensors or may ne adapted to receive information from one or more sensors. The sensors of the data gathering means may comprise one or more of the following sensors:

• A Yaw rate sensor. This may be adapted to give information on the lateral behaviour of the vehicle which helps in measuring the severity of manoeuvres. This may be enhanced with roll rate and lateral acceleration. Longitudinal acceleration may also be measured with a suitable sensor and this may be enhanced further by a sensor that measures the pitch of the vehicle. Compensation for sensors not at the centre of rotation of the vehicle may be needed.

• Vehicle location sensor. This may comprise a receiver which detects position marking signals such as those emitted by the global positioning system (GPS) and which is adapted to determine the vehicles absolute position from the signals and perhaps give speed information.

• A clock which is arranged to indicate the time of day and perhaps also the date. This could be derived from GPS information.

All the above may be provided in one self contained unit. The following additional sensors may also be provided, but most likely remote from the unit.

• A speed sensor which is adapted to indicate the speed of the vehicle relative to the road and/or relative to other surrounding vehicles.

• A driver acceleration demand sensor adapted to measure the acceleration demanded of the engine by the driver including driver demanded engine load.

• A radar sensor or a video sensor or a combined video and radar sensor which is adapted to detect the location of vehicles preceding the vehicle and/or to the side or behind it. • An emissions sensor which is adapted to measure the properties of vehicle exhaust such as a lambda sensor. Such a sensor is commonly known as a lambda sensor.

The device may include an integral power supply, possibly rechargeable batteries, or one or more terminals for connection to a power supply fitted elsewhere on the vehicle such as the vehicle battery.

The transmitter may comprise a short range transmitter which is adapted to transmit information to a receiver fitted to the vehicle that is in turn adapted to transmit the information using a long range transmitter to a device remote of the vehicle. The device may, for example include a short range transmitter that operates to the Bluetooth standard transmission. This may communicate with a Bluetooth receiver of the vehicle (where fitted) which may send information to a GSM transmitter. The information could be sent by mobile telephone across a telephony network, perhaps as a text message.

The unit may process the signals from the sensors to produce the one or more driver behaviour signals according to a set of different functions, or using fuzzy logic, look up tables, neural networks etc.

The unit may be adapted to provide metrics that indicate the drivers behaviour which are derived from the data by the data processing means in determining the driver behaviour each metric representing an area or manner of operation of a vehicle where said behaviour or driving style could have an impact on the driver's safety or impact on the environment or road traffic congestion.

The one or more signals may be representative of one or more driver metrics or representative of a combination of two or more metrics. Protection is sought for a method and unit which generates a signal that contains any combination of two or more of the following metrics, and which may present them in a report to a driver.

A non-exhaustive list of possible driver metrics (which will be understood with reference to the examples given in the specific description and drawings) contains the following:

• Longitudinal position metric;

• Lateral position metric;

• Lane selection metric; • Lane change metric;

• Acceleration metric;

• Speed metric;

• Yaw /handling metric;

• Journey ignition metric; • Traffic density metric;

• Traffic flow metric;

• Traffic discipline metric;

• Road type metric.

Some of these metrics, derived by passing different combinations of the sensed data through appropriate functions, algorithms etc indicate aspects of driver behaviour that cause pollution, and others indicate behaviour that affects levels of congestion. Still others may indicate safe driving.

Two or more of these metrics may be combined to produce at least one overall metric indicative of behaviour or the effect on congestion. The or each derived metric may be given to the driver as feedback and optionally as part of a report. The unit may determine a Longitudinal position metric which represents the headway allowed between a driver and any preceding vehicles by combining a measurement of vehicle speed V and an output signal from a vehicle radar indicative of how close to a preceding vehicle (a target T) the driver is driving.

The unit may determine a Lateral position metric which indicates how the driver is travelling relative to the lanes of a highway y combining a measurement of the position of lane boundary positions L obtained from a radar sensor relative to the position of the vehicle.

The unit may determine a Lane selection metric representing the driver's selection of lane on a multi-lane road taking into consideration the position of other vehicles by combining lane boundary position measurements with an output signal from a vehicle radar indicating the relative location of other vehicles.

The unit may determine a Lane change technique metric representing the way in which a driver changes lane from a measure of the vehicle speed V and the vehicles yaw rate or lateral acceleration during a lane change manoeuvre.

The unit may derive an Acceleration/Speed change metric by measuring the vehicles longitudinal rate of acceleration and deceleration from a signal output by a longitudinal accelerometer

The unit may derive a speed metric derived from the output of a vehicle speed sensor or measuring device.

The unit may derive a yaw rate/handling metric indicative of how much the driver swerves from side to side during a journey, and how rapidly they do so which is based on an output from a lateral acceleration sensor.

The unit may derive a journey choice metric that takes account of the type of journeys that a driver makes by combining an ignition switch on/off signal I and a clock signal t.

The unit may generate a traffic condition metric that takes into account the amount of traffic during a journey using an output from a radar sensor fitted to the vehicle which detects other vehicles. It may for instance increment a count signal each time a vehicle is detected on a journey.

The unit may generate a Traffic density metric derived from a signal output by a vehicle radar and/or information obtained from traffic cameras fitted by the road.

The unit may generate a Traffic flow metric that represents the way in which the traffic is flowing, using the output of a radar sensor and or information could be derived from road side traffic cameras.

The unit may derive a Traffic discipline metric that represents how much the driver changes lane relative to the amount of traffic based on information indicative of the number of times a driver changes lane and how much there is by combing a measurement of the lane position with a vehicle yaw measurement and the output of a vehicle radar.

The unit may determine a Road type metric based on road type as a function of vehicle position information and map data showing the location of the road on which the vehicle is travelling and its type (e.g. motorway or minor road) .

The apparatus may include interface means for connecting it to a control system of a vehicle, such as an engine management system. It may pass through this interface information which can be used by the engine management system to modify the control of the engine as a function of the measured driver behaviour.

Additionally or optionally it may include an interface to a steering system of the vehicle which may pass information that causes the steering system to modify the steering feel of the steering system.

The unit may be a self contained, partially contained or integrated unit which is fitted to a vehicle.

According to a third aspect the invention provides a driver information system for a vehicle comprising at least one driver information device fitted to a vehicle and a remote data processing device located remote of the vehicle, the driver information device comprising: data gathering means for gathering data representative of one or more operational parameters of the vehicle; processing means for processing the data to produce at least one driver signal that is representative of the drivers behaviour; and signal transmitter means for transmitting one or more of the gathered data and the driver behaviour signal to a remote receiver; the remote data processing apparatus comprising: at least one receiver located at base station which receives the data, and a driver feedback means which is adapted to process the received data and is arranged to generate at least one driver behaviour signal indicative of the driving behaviour of the driver and to feedback the signal to the driver.

The driver behaviour dependent signal that is fed back to the driver may comprise a report whose contents are dependent on driver behaviour.

There will now be described, by way of example only, one embodiment of the present invention with reference to and as illustrated in the accompanying drawings of which:

Figure 1 is an overview of a system for providing feedback on driver behaviour to a driver

Figure 2a is a schematic representation of a basic device that can be fitted to a vehicle which is in accordance with a first aspect of the invention;

Figure 2b is a schematic representation of a more advanced device that can be fitted to a vehicle which is in accordance with a first aspect of the invention;

Figure 3 is a schematic overview of the key functional parts of a processing apparatus which is arranged to receive signals from the devices of Figures 2 (a) and 2(b); Figure 4 is a more detailed schematic of the steps performed within the apparatus of Figure 3 when processing the received signals;

Figure 5 is an overview of the lane discipline metrics shown in Figure 4;

Figure 6 is an overview of the driving style metrics shown in Figure 4 style metrics;

Figure 7 is an overview of the traffic metrics shown in Figure 4;

Figures 8 to 18 comprise detailed examples of the basis for and algorithms that can be used to derive the various metrics shown in Figure 4; and

Figure 19 is an illustration of a modified arrangement in which active vehicle management to reduce emissions is provided.

As shown in Figure 1, a vehicle 10 is fitted with a driver information device (shown in more detail in Figures 2 (a) or 2(b)). The vehicle may a commercial vehicle or a privately owned vehicle, and may be a lorry, a car or a motorbike or indeed any other type of road vehicle. The device

20 includes a transmitter that enables it to send information to a remote device 30, in this case a road side antenna mounted on a pole. The antenna is connected to a network (shown by the dotted lines 40, 45) so that the signals it receives can ultimately be passed onward to a processing apparatus 50 located at a company or government office 55.

This processing unit therefore gathers information from the driver information system. This information is used to determine how the driver is driving the vehicle, and forms the basis of the generation of a report.

The report is then sent out to the driver's home 60 for review. The content of the report will vary according to the information sent to the control unit, and it is envisaged that this will be linked to whether the driver has driven well or driven badly. The apparatus on the vehicle may additionally or alternatively be used to control the performance of the vehicle in order to reduce its effect on the environment as a function of driver behaviour, again based on the content of the report for example. This may not require the need to transmit information remote from the vehicle.

As shown in Figure 2(a) , a basic driver information device 20 is a self contained unit contained by a single housing fitted to the vehicle. The only connection it requires to the outside of the unit is a power connection, and a suitable power input connector (not shown) is provided for a 12 volt power supply. Inside of the housing of the self contained unit is an electronic circuit comprising a processor 21 and an area of memory 22 connected by a bus 23. The memory 22 contains instructions 24 which are executable by the processor 21 and stored data 25 (as described later) . A unique identifier code (ID) is also written permanently into the memory of the unit.

Also within the housing are a pair of accelerometers 26, 27 that measure acceleration about two orthogonal axes. There may also be provided pitch, roll and yaw sensors. By arranging these axes with the longitudinal and lateral axes of the vehicle, the output of the sensors will respectively indicate acceleration and deceleration of the vehicle and also its movement from side to side as it swerves .

A global positioning system (GPS) receiver 28 may also be provided in the housing so that the processor can measure where the vehicle is at any moment in time. This receives signals from a set of satellites 60 as is well known in the art. A clock 29 may also be included so that the processor knows what time of day it is and also what day it is.

Finally the housing includes an (optional) transmitter 200 which is adapted to transmit information from the memory to a remote device, such as the road side receivers on their poles. Each transmission includes the unique ID code so that the information that is sent can be correlated to the vehicle. The device may have a heartbeat with data being transmitted on each heartbeat. Alternatively, it may be transmitted whenever the vehicle is stopped indicating the end of a journey. All information gathered during that journey may then be transmitted in a batch.

The processor 21 of the device 20 receives the outputs from the accelerometers 26, 27 and the GPS position signal 28 and the clock signals 29, and may store the information in a buffer in the memory 22.

A more advanced system is possible if the device includes other sensors and inputs. This may mean the device would no longer be self contained. Whilst a self contained unit is advantageous from the point of view of ease of fitting and suitability for retro-fitting to vehicles, it is limited in what can be measured.

Figure 2(b) of the accompanying drawings shows a more advanced device. Where possible like reference numerals have been used to denote like parts to ease understanding. This device is connected to a network bus 210 fitted to the vehicle 10. The network bus carries signals from different sensors and devices fitted to the vehicle, and by interrogating the signals additional useful inputs can be fed to the processor of the device. One such input can be obtained from a radar sensor 220 fitted to the front of the vehicle as part of an active cruise control or collision avoidance system. The output of the radar can be used to provide a measure of the traffic density on the road. A metric of behaviour as a function of traffic density can then be provided. Of course, video could be used instead of radar, or a combination of the two. Indeed, any other device which can sense objects around the vehicle and determine their relative position could be used.

An alternative input is a measurement of throttle position from a pedal displacement sensor 230 or throttle sensor, and perhaps the rate of change of throttle position. This can be combined with the output of an inclinometer (not shown) which determines whether the vehicle is on the flat or on an uphill section.

A still further alternative (not shown) is a feed from the ignition circuit to indicate whether the ignition is switched ON or OFF.

The component parts of the processing apparatus 50 are shown schematically in Figure 3 of the accompanying drawing. This gives a top level view of the apparatus (a more detailed representation of its function being given in Figure 4) . The apparatus comprises a processor 51 connected to a memory 52 across a bus and a receiver 53 for incoming information. In the memory are stored program instructions 54 for the processor and a database of driver data 55 derived at least partially from the incoming information. This data is referenced by driver ID and as such will indicate the owner of the vehicle which has transmitted information by their name and postal address or email address. This personal information can be obtained through initial registration to the system, for example when purchasing or using a driver information device for the first time.

The apparatus 50 is adapted to receive the information from the vehicle device 20. In practice it will receive information from many hundreds of vehicles fitted with driver information devices. The ID code is extracted from the incoming information so that the information can be linked to an individual vehicle. Having received the information it then processes the information to determine a set of driver behaviour metrics. These metrics are then combined in sets until they are ultimately combined to produce pollution metric and congestion metric. These are stored in the database and indexed by the driver ID code.

The individual driver behaviour metrics may be calculated periodically, and in their calculation may take into account previously calculated driver behaviour metrics. This will allow a running average to be established. Alternatively, a series of overall driver behaviour metrics may be calculated for any given journey or set of journeys. They may be calculated each time data is received.

As shown in Figure 3 and 4 of the accompanying drawings, the gathered information is input to the apparatus 50, which determines driver behaviour metrics that in turn are fed into a function which can be presented in a report. The apparatus then combines the content of the report with the personal address information stored in the database and passes them to an output device 56 such as a printer to produce the report 57.

A number of metrics may be determined that indicate driver behaviour. These can be determined in a number of different ways including the use of rules, look up tables, fuzzy logic, neural networks and genetic algorithms. The skilled man will appreciate which is best to use when presented with the signals for input and the desired metric required for an output. Each of the metrics can be grouped into a set with similar metrics, and in this example the three sets are: Lane discipline metrics, driving style metrics, and traffic condition metrics.

1 Lane discipline metrics

These metrics are summarised in Figure 5 of the accompanying drawings. Each one indicates the driver's behaviour in relation to driving on a highway. A metric will indicate good behaviour if the driver is driving in a safe and courteous manner and one in which they are least likely to disrupt traffic flow and create accidents. A bad behaviour represents an inconsiderate or dangerous driver who is likely to cause accidents and impede traffic flow through their driving.

1.1 Longitudinal position.

This metric 101 represents the headway allowed between a driver and any preceding vehicles. It requires as an input a measure of the vehicle speed V, and an output signal from the vehicle radar to indicate how close to a preceding vehicle (a target T) the driver is driving. If the driver is always close to preceding vehicles this metric will indicate bad behaviour, if a good spacing is kept the behaviour will be indicated as good. Both an instantaneous and a trend (average) metric can be produced

The behaviour measured by this metric is illustrated by example in Figure 8 (a) . To the left a vehicle 80 can be seen driving a safe distance dl behind a preceding vehicle 81. This vehicle is considered to be driving safely and so the metric will correspond to good behaviour. On the other hand the vehicle 81 is driving at too close distance d2 to a preceding vehicle 82, and the metric for this vehicle would indicate that it is driving badly. A suitable algorithm 83 for calculating this metric is shown in Figure 8(b) of the accompanying drawings. Note that the output can be filtered to give a trend metric as well.

1.2 Lateral position

This metric 102 indicates how the driver is travelling relative to the lanes of a highway. It uses as its input a measure of the lane boundary positions L obtained from the radar sensor. If the vehicle is located centrally between lane boundaries the metric will represent good driving. If the vehicle is veering towards or even straddling the boundaries it will be considered bad.

The behaviour represented by this metric is shown in the example of Figure 9 (a). A vehicle 90 travelling in the middle of a lane, as identified by boundaries 91 and 92, is considered to be good driving. Other cars 93, 94 that are not in the middle are considered bad driving. A suitable algorithm for calculating this metric is shown in Figure of the accompanying drawings.

The algorithm provides a deadband i.e. region around the middle of the lane where driving is good. Driving outside the deadband is penalised (e.g. could be a non-linear increasing relationship e.g. at 1, 1.5, 2m from the lane centre the penalty maybe 0, 1, 4units) .

1.3 Lane selection

This metric 103 represents the driver's selection of lane on a multi-lane road taking into consideration the position of other vehicles. For the metric to indicate good driving the vehicle should either be in the inside lane if there is little preceding traffic, or in another lane if there is a preceding vehicle in the inside lane. If there are no close preceding vehicles and the vehicle is not in the inside lane (so called middle or outside lane hogging) the metric will indicate bad behaviour.

The behaviour measured by this metric is shown in the example of Figure 10 of the drawings. As can be seen a vehicle 110 travelling in the inside lane is considered to be well driven. A vehicle 120 driven in the middle lane when there is nothing to overtake is considered to be badly driven. Note that if vehicle 110 pulled out to overtake vehicle 130 it may still be represented as well driven as there is a reason to be in the middle lane. A suitable algorithm for calculating this metric is shown in Figure 10 (b) of the accompanying drawings. It requires as its input a radar signal indicating the position of preceding traffic targets T, and either lane boundary information L or other indication of lanes, e.g. GPS data G plotted on a suitable map of lanes.

In this arrangement a box region is to be added to the road. Input to the function would be a flag indicating that the box is occupied or not. If the box isn't occupied then the metric is a function of the length of time that the box is unoccupied, (e.g. times of 1, 2, 3s could have a penalty of 0, 1 , 4units etc) .

1.4 Lane change technique

This metric 104 represents the way in which a driver changes lane. A harsh and sudden swerve from one lane to the next will represent bad behaviour, a gentle swing from one lane to the other good behaviour.

This can be derived from a measure of the vehicle speed V and the vehicles yaw rate or lateral acceleration during the manoeuvre. Such manoeuvres can readily be identified as the vehicle will typically swing one way then the next before travelling straight again. An example of the behaviour exemplified by this metric is shown in Figure 11 (a) of the accompanying drawings. A vehicle 1100, 1100' starts in the middle lane at time and position A and moves gradually to the inside lane at time and position B. This is considered good behaviour. Alternatively, a vehicle 1110, 1110' moves from position C to position D in a sharp manner, swerving dangerously. This is considered to be bad driving.

A suitable algorithm for calculating this metric is shown in Figure ll(b) and (c) of the accompanying drawings. Figure ll (b) shows how the number of changes can be taken into consideration, and ll(c) the severity of the changes.

2 Driving style metrics

These metrics indicate the driver's general behaviour in relation to driving on a highway. A good driver will be one who drives in a way which minimises fuel consumption and has a smooth style. A poor driver is one who is driving aggressively or erratically.

2.1 Acceleration/Speed change metric

This is a relatively simple metric 201a obtained by measuring the vehicles longitudinal rate of acceleration and deceleration A" . As such it can be obtained simply using the output of the longitudinal accelerometer.

Additionally or alternatively, a speed based metric 201b derived from the vehicles speed V can be used. Rapid changes in speed of the vehicle will be represented in the metric as a bad behaviour, steady speeds and gradual changes as a good metric. As shown in Figure 12, a trace 1210 corresponding to lots of rapid changes in speed/acceleration will be considered to represent bad behaviour. One that is smoother, such as trace 1220 will be considered to represent good behaviour.

A typical plot of speed is shown in Figure 13 of the accompanying drawings. In the speed plot of Figure 13, an additional variable representing the speed limit Vmax is also shown. The metric will represent bad behaviour as shown in trace 1300 or good behaviour as shown in trace 1310, i.e. below or above the speed limit. This information can be derived from GPS position information cross referenced to a map of the roads and their limits .

A driver who uses only small throttle openings unless on a steep hill may then be considered to be using good driver behaviour, and one who makes large throttle openings considered to be using bad driver behaviour.

Figures 16 and 17 illustrate functions that can be used to derive these two metrics. As with the other metrics, a filtered output is provided to give average trend information.

2.2 Yaw rate/handling metrics

This metric 202 is a generalised indication of how much the driver swerves from side to side during a journey, and how rapidly they do so. The more they swerve the more the metric indicates bad driving, the less they swerve the more it indicates good driving. The input to this metric is the lateral acceleration A' .

This is shown by example in Figure 14 of the accompanying drawings. Trace 1410 represents good driving as the vehicle is maintaining a steady smooth course. Trace 1420 is considered bad driving, as the course is very erratic with many rapid changes.

A suitable function for determining this metric is shown in Figure 18 of the accompanying drawings.

2.3 Journey choice metrics

This metric 203 takes account of the type of journeys that a driver makes. Short duration, short distance journeys made frequently will be considered bad behaviour as they could be made without the use of vehicle. Long journeys will be considered good behaviour. This distinction takes account of the low efficiency of vehicles during their warm up phase, making long journeys better for the environment than short ones (on a mile per mile comparative basis) . The input to this metric is the ignition switch on/off signal I and the clock signal t.

This metric is illustrated in Figure 15. To the left of the plot are the traces of two long journeys 1510. To the right are the plots of several short ones 1520. The behaviour to the right 1510 is considered better.

3 Traffic condition metrics

These traffic condition metrics take into account the amount of traffic during a journey. Unlike the previous two types (lane discipline and driving style) they relate mostly to congestion and less so to environmental issues or safety. Driving when there is little traffic, for example on quiet roads or late at night, can be considered to be good behaviour. Driving on busy roads in rush hour can be considered bad for congestion and hence bad behaviour. 3.1 Traffic density metric

This metric 301 considers how much traffic is on the road when a driver is driving. It can obtain this information from the vehicle radar, although it could also be obtained from traffic cameras fitted to the road. The more vehicles, the more the metric indicates bad traffic, the less then the more it indicates good traffic density. It requires as its input only a measure from the radar as shown in Figure 7 of the accompanying drawings.

3.2 Traffic flow metric

This metric 302 represents the way in which the traffic is flowing. If the traffic is moving very slowly relative to the speed limit on a particular road, it can be considered to be flowing badly. If the speed is high the flow can be considered to be good. Both an instantaneous and trend metric may be produced. Only the output of the radar sensor is needed, although again this information could be derived from road side traffic cameras .

3.3 Traffic discipline metric

This metric 303 represents how much the driver changes lane relative to the amount of traffic. It requires as an input a measure of the frequency and number of times a driver changes lane and how much traffic there is derived from the vehicle radar. A driver changing lanes lots of times in busy traffic, weaving in and out of gaps, can cause panic braking from other drivers and lead to queues developing. This metric will represent such driving as bad. A driver who maintains a steady position in one lane will be considered good. 3.4 Road type metric

This metric 304 is based on road type and can be derived as a function of the position information and map data showing the location of the road on which the vehicle is travelling and its type (e.g. motorway or minor road) . This is shown in Figure of the accompanying drawings.

An overview of these different metrics and how they are processed by the control unit is shown in Figure 4 of the accompanying drawings. This shows how the metrics in each group are combined to give a pollution metric and the traffic metrics are combined to give a congestion metric.

The pollution and congestion metrics are then also combined to produce a single driver behaviour value which is feedback to the driver and provides a report of information.

To the left of the Figure 4 are the input signals. Some of these feed into functions representing metrics of the driver behaviour model, whilst others feed into functions which represent metrics of the traffic model. The driving behaviour metrics of both the driver behaviour models are then combined to form the basis of a pollution metric, whilst the traffic model goes on to form the basis of a congestion contribution metric. The metrics may, for example, each represent good to bad driving on a scale from one to ten. They may then be combined simply by calculating an average value, or perhaps a weighted average. The two overall metrics are then used to produce an overall metric which can be presented in a report.

It will be appreciated that a number of modifications are possible. One such modification is for the driver information unit to calculate the driver behaviour metrics itself and only send these to the controller. This can be done periodically, e.g. after each journey or perhaps at the end of each day. An advantage to such an arrangement is that the behaviour metric can then be presented to the driver in real time on the vehicle. A traffic light scheme of red, amber and green lights could be used- red indicating bad driving and green good. This may help to encourage the driver to drive better.

Generally, a set of driver metrics which all indicate bad behaviour whilst the traffic model also indicates heavy congestion will combine to give a favourable report for the driver. A set of good driver behaviour metrics and a traffic model that corresponds to light traffic will give a less favourable report.

It is expected that by providing feedback based on behaviour, a reduction in congestion and fuel consumption can be achieved since drivers that behave in such a way will be encouraged. This will lead to the more efficient operation of the vehicle reducing costs and also reducing wear on the vehicle and improving safety as well as reducing the impact on the environment.

In a further modification shown in Figure 19, the apparatus 20 of Figure 2 can be interfaced to one or more vehicle control systems. In this example it is interfaced to the engines electronic control unit (ECU) 1900 and also the vehicles power assisted steering 1950. It may interface using the vehicles CAN network where provided or any similar interface. The apparatus 20 is adapted to pass parameters across the interface to the ECU 1900 and steering control system 1950 as a function of the measured parameters, and hence as a function of the driver behaviour.

The ECU 1900 is arranged to modify the operation of the engine 1960 in response to the received parameters. In particular, it may limit the maximum engine revs available, the peak torque, the fuel/air mixture and the maximum vehicle speed. These modifications may be made as a function of any of the measured parameters with the aim of optimising the engine for emissions for a given set of circumstances. It may for instance reduce the engines performance or vehicle speed if the drivers behaviour is considered to be bad for the environment.

The steering system controller may be similarly arranged to modify the steering feel of the steering 1970 as a function of the parameters passed to it, with a goal of encouraging more smooth steering inputs from the driver. This can be achieved by varying the steering feel to one more conducive to smooth steering under certain conditions.

It is to be noted in this arrangement that the feedback to the driver will be provided through their feel of the change in the vehicles behaviour. Also the connection to the remote server could be omitted making the apparatus self-contained.

By providing apparatus that alters the operation of the vehicle as a function of driver behaviour so as to reduce the impact on the environment and encourage better behaviour, the overall effect of increased vehicle usage can be mitigated. This also allows the performance of the vehicle to be maintained for those circumstances where good behaviour is measured or conditions are favourable (such as periods of low congestion or in non-built up areas or the like) and as such provides a reward to a considerate driver. The applicant is the first to appreciate that such driver and condition dependent modifications can be used to encourage a change in behaviour leading to reduce emissions and reduced harm to the environment.

Claims

1. A method of operating a vehicle being driven along a road by a driver comprising, whilst the vehicle is being driven: gathering data whilst the vehicle is being driven indicative of the manner in which the vehicle is being operated using a driver information device fitted to the vehicle; processing the data gathered by the device whilst the vehicle is being driven or afterwards or a combination of both to produce a signal representative of the manner in which the vehicle is being operated, the signal comprising at least one metric indicative of driver behaviour and/or congestion on the road at the time; and providing feedback to the driver indicative of the manner of operation, so as to modify the manner in which the driver operates the vehicle according to the at least one metric that is fed back to the driver.

2. The method of claim 1 which further comprises modifying the manner in which the vehicle is functioning so as to give feedback which influences the drivers behaviour in a manner which tends to lead to a modification of the driver behaviour metric which in turn tends to optimise the operation of the vehicle.

3. The method of claim 1 or 2 in which the feedback is presented as a report.

4. The method of any preceding claim which comprises giving feedback to the driver in the form of presenting a display to the driver whilst they are driving.

5. The method , of any preceding claim which comprises giving feedback to the driver by modifying at least one operational parameter of the vehicle as a way of modifying the manner in which the vehicle is driven.

6. The method of claim 5 which comprises modifying the manner in which the vehicle is driven by altering the fuel mixture fed to the engine of the vehicle, making it run more leanly to reduce emissions when the driver is exhibiting bad behaviour.

7. The method of any preceding claim which comprises modifying the manner in which the vehicle is driven by altering the feel of a steering system fitted to the vehicle.

8. The method of any preceding claim which comprises disabling the vehicle either completely or partially in the event that driver behaviour which is consistently bad for the environment is detected.

9. The method of any preceding claim in which the method comprises determining one or more driver metrics and presenting at least one such metric in the report.

10. The method of claim 9 in which the metrics comprise one or more of the following: a Longitudinal position metric, a Lateral position metric, a Lane selection metric, a Lane change metric, a Acceleration metric, a Speed metric, a Yaw/handling metric, a Journey ignition metric, a Traffic density metric, a Traffic flow metric, a Traffic discipline metric and a Road type metric.

11. The method of claim 10 which further comprises determining a combined metric representative of a combination of two or more metrics and providing the combined metric to the driver as feedback.

12. The method of any preceding claim in which the steps of determining the driver behaviour signal and/or metrics are performed remote from the vehicle.

13. An onboard vehicle processing unit for fitment to a vehicle comprising: data gathering means for gathering data representative of one or more operational parameters of the vehicle; processing means for processing the data to produce a driver behaviour signal defining at least one metric representative of the manner in which the driver is driving the vehicle; and feedback means for providing feedback to the driver dependent upon the driver behaviour signal.

14. An on-board vehicle processing unit according to claim 13 which further comprises modifying means adapted to modify one or more operational parameters of the vehicle as a function of the driver behaviour signal, the functions affecting the amount of impact the vehicle has on the environment so as to encourage good driver behaviour.

15. The vehicle controller of claim 13 which further includes a communication means for passing one or more of the gathered data and the driver behaviour signal to a remote receiver.