GB2539470A

GB2539470A - Monitoring vehicle behaviour

Info

Publication number: GB2539470A
Application number: GB1510655.2A
Authority: GB
Inventors: Gilbert Wayne; Cowper Steve
Original assignee: RISK TELEMATICS UK Ltd
Current assignee: RISK TELEMATICS UK Ltd
Priority date: 2015-06-17
Filing date: 2015-06-17
Publication date: 2016-12-21
Also published as: GB201510655D0

Abstract

A method/apparatus for monitoring vehicle behaviour comprises receiving accelerometer data and corresponding location data from a plurality of vehicles 402. For each vehicle the accelerometer data is associated with a road segment based on the corresponding location data 404. A profile of acceleration data is then determined for the one or more road segments 406. It is then determined if the accelerometer data from the one or more vehicles in the one or more road segments deviates from the profile by more than a threshold level 408. The threshold level may be determined in accordance with a known property of the road. If the accelerometer data deviates by more than the threshold level an alert may be generated or a control function may be applied to the particular vehicle which may activate the brakes. A control function may be applied to an item of traffic infrastructure in the event that the accelerometer data deviates from the profile by more than the threshold level.

Description

Monitoring Vehicle Behaviour The invention relates to a method and apparatus for monitoring the behaviour of a vehicle.

Automotive telematics apparatus are used for driver behaviour analysis in the insurance industry. Such analysis enables the risk associated with a particular driver to be determined on an objective basis based on actual driving, rather than a prediction based on demographic information, for example.

io Vehicle telematics apparatus provide information regarding driver behaviour that may be analysed after a collision or period of driving, but do not give any details regarding the traffic conditions in which the vehicle was driving. A problem with such systems is that the risk associated with the behaviour of the vehicle is interpreted without knowledge of circumstances that may have given rise to what appears to be reckless behaviour.

According to a first aspect of the invention there is provided an automated method for monitoring vehicle behaviour, comprising: receiving accelerometer data and corresponding location data from a plurality of vehicles; for each vehicle, associating the accelerometer data with a road segment based on the corresponding location data; determining a profile of accelerometer data for one or more road segments; determining if accelerometer data from one or more vehicles in the one or more road segments deviate from the profile by more than a threshold level.

By comparing the accelerometer data from one or more vehicles with the profile, the method can assess the behaviour of the one or more vehicles in the context of current or historical traffic conditions. For example, the use of sudden braking may be unavoidable where similar braking is being applied by other vehicles on a road segment.

The accelerometer data may comprise one or more of vehicle braking, vehicle forward acceleration, vehicle lateral acceleration, and vehicle vertical acceleration. Other data, such as speed data, may be included in the profile. The method may comprise determining if the accelerometer and other data from one or more vehicles in the one or more road segments deviate from the profile by more than a threshold level.

The method may further include generating an alert if the accelerometer data from the one or more vehicles deviates from the profile by more than the threshold level. The method may further include applying a control function to a particular vehicle in the event that the accelerometer data of the particular vehicle deviate from the profile by more than the threshold level. The method may further include generating a vehicle use profile by aggregating said deviations from the profile for a particular vehicle. The vehicle use profile may assist in determine the driving style of a vehicle and so be correlated to the risk of the vehicle being involved in a road traffic collision. The method may further include applying a control function to the particular vehicle if the aggregated deviations exceed a to predetermined control envelope. The method may further include applying a control function to an item of traffic infrastructure in the event that the accelerometer data deviate from the profile by more than the threshold level. Generating an alert or controlling a vehicle or piece of infrastructure in real time may reduce the risk of a road traffic collision, ease traffic flow and reduce overall fuel consumption.

The profile may comprise accelerometer data from a single vehicle, a plurality of vehicles, or a single vehicle other than the one or more vehicles. The profile may be a statistical profile. The threshold may be determined in accordance with a known property of the road.

According to a second aspect of the invention there is provided a vehicle monitoring apparatus comprising: a database of accelerometer data profiles in which each profile is associated with one or more road segments; one or more receiver units configured to receive a vehicle position and a vehicle acceleration along at least one axis associated with a vehicle; a processor configured to determine a particular road segment associated with the vehicle based on the vehicle position and further configured to determine whether the vehicle acceleration deviates, by more than a threshold level, from a corresponding profile in the database associated with the particular road segment; and an alert generator configured to generate an alert in the event of a said deviation in vehicle acceleration.

The vehicle monitoring apparatus may comprise a position determining unit configured to determine a position of the vehicle. The vehicle monitoring apparatus may comprise an accelerometer configured to determine vehicle acceleration along at least one axis.

The one or more receiver units may be configured to receive a vehicle position and a vehicle acceleration along at least one axis from a plurality of vehicles. The processor may be configured to determine a particular road segment associated with each of the plurality of vehicles based on the vehicle positions associated received from the vehicles.

The processor may be configured to determine whether each of the vehicle accelerations of the vehicles deviates, by more than a threshold level, from a corresponding profile in the database associated with the particular road segment in which that particular vehicle is located. The vehicle monitoring apparatus may comprise a database generator configured to generate the database of accelerometer data profiles based on the vehicle positions and vehicle accelerations received form the plurality of vehicles.

According to a third aspect of the invention there is provided a portable device for use in a vehicle comprising: a position determining unit configured to determine a vehicle position; and an accelerometer configured to determine vehicle acceleration along at least one axis; a transmitter configured to transmit the vehicle position and vehicle acceleration to a vehicle monitoring apparatus, such as the vehicle monitoring apparatus according to the third aspect; and an alert receiver configured to receive the alert from the vehicle monitoring apparatus.

The portable device may be installed or mounted in the vehicle. The portable device may comprise a control module configured to apply a control function to the vehicle in response to an alert from the alert generator.

Embodiments of the invention will now be described, by way of example, with reference to the following figures, in which: Figure 1 illustrates a block diagram representation of a remote vehicle monitoring 30 apparatus; Figure 2 illustrates a block diagram representation of a portable device for providing in a vehicle; Figure 3 illustrates a block diagram representation of a vehicle monitoring apparatus provided within a vehicle; Figure 4 illustrates a flow chart of a method for operating the vehicle monitoring apparatus of figure 1 or figure 3; and Figure 5 illustrates a schematic map of a road network.

Figure 1 illustrates a block diagram representation of a remote vehicle monitoring apparatus 110. The vehicle monitoring apparatus comprises a database of accelerometer data 112, a processor 114 and a telemetry unit 116. The vehicle monitoring apparatus 110 is remote from a plurality of vehicles 118, 120, 122 in this example and may be provided on a server.

The telemetry unit 116 comprises a receiver that is configured to receive, from a plurality of portable devices 119, 121, 123 installed in the vehicles 118, 120, 122, a vehicle position and a vehicle acceleration along at least one axis. An example of a portable device is described with regard to figure 2 below.

A database generator 124 is configured to generate the database of accelerometer data 112 based on the vehicle positions and vehicle accelerations received form the plurality of vehicles 118, 120, 122. Each item of accelerometer data in the database of accelerometer data 112 is allocated to a road segment. An item of accelerometer data may be a vector, comprising magnitude and direction information, or a scalar value of the magnitude of an acceleration. The items in the database may be representative of the most recent accelerometer data received from the vehicles 118, 120, 122, which may be considered as current accelerometer data. As new data is acquired, the current data in the database may be replaced. Alternatively, as new data is acquired it may be added to the database as current data and older data in the database may be retained and considered as historical data.

The database generator 124 is further configured to determine a profile of accelerometer data for one or more road segments. The profiles may be provided as entries in the database of accelerometer data 112. Each profile relates to the received accelerometer data from vehicles 118, 120, 122 in that road segment and may be based on current acceleration data, historical acceleration data or both current and historical acceleration data.

The processor 114 is configured to determine a particular road segment associated with each of the plurality of vehicles 118, 120, 122 based on the vehicle positions associated received from the vehicles 118, 120, 122. The determination of the respective road segments may be achieved by comparing a GPS-type positions of the vehicles 118, 120, 122 with a vector road map. The heading of each vehicle may be used to determine which carriageway that vehicle is traveling on.

The processor 114 is also configured to determine whether each of the vehicle accelerations of the vehicles 118, 120, 122 deviates, by more than a threshold level, from a corresponding profile in the database associated with the particular road segment in which that particular vehicle 118, 120, 122 is located. The threshold level may be static, or may depend on contextual information, such as the prevailing weather conditions and whether the vehicle is in a traffic accident black spot.

An alert generator 126 is configured to generate an alert in the event that a deviation in a vehicle acceleration is determined by the processor 114. The alert can be in the form of an entry in the database 112, a visual output at the vehicle monitoring apparatus 110, a visual output in the vehicle or a visual output on a dynamic piece of traffic infrastructure such as an electronic sign or traffic light. Where the desired alert is an actuation of a control system within the vehicle, such as the vehicle brakes, the alert generator 126 may comprise a transmitter to send a control signal to a control module within the vehicle 122.

In practice, the vehicle monitoring apparatus 110 may be distributed in a cloud computing architecture in order that the apparatus may be dynamically scaled to monitor a desired number of vehicles. Many hundreds or thousands of vehicles may be monitored simultaneously by such an apparatus. 'Big data' processing services such as the Amazon® KinesisTM service (http://aws.amazon.com/kinesis) may be used to implement the vehicle monitoring apparatus 110 in order to perform real time traffic analysis.

Such data processing services enable a data scoop to be set up for each segment of a road network and monitor incoming data streams from in-vehicle accelerometers in real time. Each data scoop only monitors events that occur within its segment, although road segments can be combined to produce aggregated data. In the United Kingdom, for example, there are approximately 10 million separate road segments, each of which are separated by junctions. A road segment can be considered to be a section of road which has a single entry point and a single exit point and which has a uniform road type classification and speed limit. A new segment may be required whenever there is a one or more of the following conditions: * a change in road type (single carriageway becoming dual carriageway for

example);

* a change in the speed limit; * a junction (for example a side road, T-junction, slip road); or * a significant distance (for example stretches of motorway between junction which may be several miles long will be broken into individual segments).

Within the road network, the map of road segments may be contiguous, meaning that all segments can be connected to the overall network and navigable by vehicles.

In addition to accelerometer data, other data may also be reported to the vehicle monitoring unit 110 by the vehicles 118, 120, 122 and this data may be accounted for when building the database and by the determinations made by the processor 114. Examples to of such other data include the speed of the vehicle, heading of the vehicle, a servicing condition of the vehicle or status information regarding a vehicle system, such as the tyres, brakes, battery or lights.

Figure 2 illustrates a block diagram representation of a portable device 200 for providing in a vehicle 222 and communicating with the vehicle monitoring apparatus of figure 1. The portable device 200 comprises a position determining unit 230, an accelerometer 232 and a transceiver 234.

The position determining unit 230 is configured to determine a vehicle position and may be provided by a global positioning system (GPS) or Galileo unit, for example.

The accelerometer 232 is configured to determine vehicle acceleration along at least one axis. The accelerometer 232 may, for example, provide two or three dimensional accelerometer information in orthogonal axes. The portable device 200 may be installed, or mounted, in the vehicle 222 in order to reduce dampening of the accelerometer data.

The transceiver 234 comprises a transmitter and a receiver and may be provided by a telecommunications device that operates using 2G, 3G, 4G or 5G mobile telecommunications standard signals, for example. The transmitter is configured to transmit the vehicle position and vehicle acceleration to the vehicle monitoring apparatus described with reference to figure 1.

An optional control module 236 is configured to apply a control function to the vehicle 222 in response to an alert from the alert generator of the vehicle monitoring apparatus being received by the receiver. The control module 236 may be configured to operate the throttle, brakes or transmission system of the vehicle 222. If the optional control module 236 is not provided then the transceiver 234 may be replaced by a transmitter without a receiver.

The portable device 200 may be configured to provide other data to the vehicle monitoring apparatus in addition to the accelerometer data. The other data may be obtained directly for the bus of an on-board electronic vehicle control unit, such as the engine control unit (ECU), or by obtaining data from an on-board display of the vehicle, such as the dashboard. In principle, any information that is displayed to the driver or obtainable from the ECU bus may be provided as the other data. Other data may also be reported to the vehicle monitoring unit by the vehicles and this data may be accounted for when building the database and by the determinations made by the processor.

Figure 3 illustrates a block diagram representation of another vehicle monitoring apparatus 300. The vehicle monitoring apparatus 300 in this example is configured to be installed or mounted within a vehicle 322.

The vehicle monitoring apparatus 300 comprises the components of the vehicle monitoring apparatus of figure 1 and, in addition, a position determining unit 330 and an accelerometer 332. Corresponding series of reference numerals are used between figures 1 and 3 to refer to similar component.

The position determining unit 330 is configured to determine a position of the vehicle 322 in which the vehicle monitoring apparatus 300 is installed or mounted. The accelerometer 332 is configured to determine a vehicle acceleration along at least one axis of the vehicle 322. The axis of acceleration may run from the front to the back of the vehicle and may be orthogonal to the axis of a pair of non-steering wheels of the vehicle 332 and to an axis normal to the ground.

In this example, the processor 314 is configured to determine a particular road segment in which the vehicle 323 is located based on the position of the vehicle 323 determined by the position determining unit 330. The processor 314 is also configured to determine whether the vehicle acceleration determined by the accelerometer 332 deviates from a corresponding profile in the database 312 associated with the particular road segment by more than a threshold level.

The alert generator 326 is provided within the vehicle 322 in this example and so may provide an alert to a driver of the vehicle 322. A control module may also be provided to apply a control function to the vehicle 322 in response to an alert from the alert generator 322.

Figure 4 illustrates a flow chart of a method 400 for operating the vehicle monitoring apparatus of figure 1 or figure 3, which relates to an automated method for monitoring vehicle behaviour.

The method 400 comprises receiving 402 accelerometer data and corresponding location data from a plurality of vehicles, and for each vehicle, associating 404 the accelerometer to data with a road segment based on the corresponding location data. The accelerometer data may contain items of information as discussed with reference to figure 1. A vector or scalar description of a state of acceleration of a vehicle is an example of an item that may be included in the accelerometer data. Each item may be associated with a particular vehicle, a position of that vehicle and a time of acquisition. The most recent item of data, or a predetermined number of recent items of data, from a particular vehicle may be considered as current acceleration data for that vehicle, for example. The accelerometer data may therefore relate to current acceleration of the respective vehicles. Subsequently to the current acceleration data being received it can be stored as historical acceleration data. The accelerometer data may comprise one or more of vehicle braking, vehicle forward acceleration, vehicle cornering (lateral acceleration), and vehicle vertical acceleration.

A profile of accelerometer data is determined 406 for each road segment. Each profile relates to the received accelerometer data from vehicles in that road segment. For example, the profile may be based on current acceleration data, historical acceleration data or both current and historical acceleration data. The profile may be a statistical profile that may comprise a mean, median, mode or range of accelerations in a particular road segment. In a simple case, the profile may comprise accelerometer data from a single vehicle. The profile for a road segment may contain acceleration data only from vehicles in that road segment or it may include acceleration data from one or more neighbouring road segments of each road segment.

Mapping adjacent segments that are connected to a particular segment can enable not only determination of travel direction but also the evolution of improved 'average' metrics based on a segment and its neighbour. Groups of segments can be clustered as an additional layer of data which can be analysed. Analysis of groups of segments may enable improved analysis of busy junctions, for example, or where the data for historical crash information is not available at a single road segment level, but exists for a number of segments joined together. Analysis of groups of segments also allows the number of braking events to be monitored within a linked section of segments which historically have had a high incidence of serious crashes.

The method 400 includes determining 408 if accelerometer data, and optionally other data, from a particular vehicle, or a sub-set of vehicles, in a particular road segment or segments deviates from the profile by more than a threshold level.

In the case where the profile comprises current accelerometer data, the method 400 can assess the behaviour of the one or more vehicles in the context of current traffic conditions by comparing the current accelerometer data from the vehicles with the profile. For example, the use of sudden braking may be unavoidable where similar braking is being applied by other vehicles on a road segment. The analysis of current accelerometer data is may be achieved by performing the method 400 in real time. Alternatively, the method 400 or steps therein may be performed substantially later than the instant that the accelerometer data is acquired.

In the case where the profile comprises historical accelerometer data, the method 400 can assess the behaviour of the vehicle in the context of usual or typical vehicle behaviour for a road segment. For example, a windy road may require all road users to accelerate and decelerate more than is necessary for a straight road. Knowledge of historical behaviour of traffic on a particular road segment enables the method to account for underlying road conditions when monitoring the vehicle behaviour.

The profile or the threshold to apply can be determined in accordance with a known property of the road, which may offer contextual information that is useful in determining the appropriate action to take. Such known properties may include the speed limit, type of road, accident history of a road segment (whether it is an accident "black spot"), presence of traffic calming or monitoring measures (such as speed cameras), or the prevailing weather condition. For example, a greater statistical variance (larger threshold) may be allowed for one type of road, such as a multiple carriageway road, than another, such as a single carriageway road.

An alert may be generated by the alert generator if the accelerometer data from one or more vehicles does deviate from the profile by more than the threshold level.

A control function of a particular vehicle may be applied by the control module in the vehicle in response to the alert. For example, the brakes or accelerator of the vehicle may be applied automatically by the control module, or the control module may change a gear of the vehicle in response to the alert. The control module may also control the particular vehicle if the aggregated deviations exceed a predetermined control envelope.

In addition to, or as an alternative to controlling the vehicle, the alert generator may control an item of traffic infrastructure in the event that the accelerometer data deviate from the profile by more than a threshold level. For example, a dynamic road sign may be used to provide a warning message to drivers of vehicles or the state of a traffic light may be set to stop traffic flow in the vicinity of a deviant vehicle, for example.

A use profile of a vehicle can be generated by aggregating the deviations by that vehicle from the profile determined from accelerometer data from a plurality of vehicles. The use profile may be stored either in a portable device in the vehicle or at a remote vehicle monitoring apparatus. The use profile provides an indicator of the style of driving that the vehicle has been subjected to and so may be used as an indicator of the likelihood of the vehicle being involved in an accident.

Figure 5 illustrates a schematic of a map of a road network 500. The road network 500 has a dual carriageway road, a fast country lane and an urban area. The dual carriageway road has a first southbound segment Si, a second southbound segment S2 and a north bound carriageway segment S3. A segment of road can be considered to be a portion of road bounded by junction nodes. The first southbound segment S1 and the second southbound segment S2 are joined at an exit junction J1 that leads onto a first segment S4 of the fast country lane. A second junction J2 separates the first segment S4 and a second segment S5 of the country lane. The second junction J2 also leads onto an urban road segment S6 that terminates at a third junction J3.

The dual carriageway road has a variable speed limit that can be set by the information displays 11, 12 separately for the north and southbound carriageways. A national speed limit for a dual carriageway road applies if the information displays 11, 12 are not in use, which may be 70 miles per hour, mph (about 110 kilometres per hour, kph). The single carriageway country road has a lower speed limit of 60 mph (about 100 kph). The urban road segment S6 has a speed limit of 30 mph (about 50 kph).

The road network 50 contains several dozen vehicles that each report accelerometer data to a vehicle monitoring apparatus such as that described with reference to figure 1. A number of vehicles V1-V8 that are fitted with portable devices such as those described with reference to figure 2 are illustrated travelling in the road network. The arrow on each vehicle V1-V8 represents the direction of its (positive) acceleration. The speeds and accelerations of the illustrated vehicles V1-V8 in this example are listed below.

Vehicle Speed Acceleration V1 69 mph (111 kph) +0.5 mph.s-1 (0.23 m.s-2) V2 72 mph (116 kph) +1 mph.s-1 (+0.45 m.s-2) V3 84 mph (135 kph) -3 mph.s-1 (-1.3 m.s-2) V4 56 mph (90 kph) 0 mph.s-1 (0 m.s-2) V5 56 mph (90 kph) 0 mph.s-1 (0 m.s-2) V6 30 mph (48 kph) 0 mph.s-1(0 m.s-2) V7 30 mph (48 kph) 0 mph.s-1(0 m.s-2) V8 28 mph (45 kph) -6 mph.s-1 (-2.6 m.s-2) The vehicle monitoring apparatus receives accelerometer data and corresponding location data from a plurality of vehicles V1-V8.

For each vehicle V1-V8, the apparatus associates the accelerometer data with a road segment 51-S6 in which the vehicle is travelling based on the location of the vehicle. The direction of travel may also be used in addition to the location in order to determine which road segment a vehicle is travelling on. In this example, the direction part of the velocity vector associated with a first vehicle V1 enables the apparatus to determine that the first vehicle V1 is travelling on the southbound carriageway segment S1 rather than the northbound carriageway segment S3. Similarly, the direction part of the velocity vector associated with a fourth vehicle V4 enables the apparatus to determine that the fourth vehicle V4 is travelling on the northbound carriageway segment S3 rather than the southbound carriageway segment Si.

Using the accelerometer data from these vehicles, the processor determines a statistical profile of accelerometer data for each road segment on which at least one vehicle is travelling.

Each of the first second and third vehicles V1-V3 are located on the first segment S1. A number of other vehicles (not shown) may also be on the first segment S1. For each of the first second and third vehicles V1-V3, the processor determines whether the acceleration of that particular vehicle deviates from the statistical profile of acceleration in the first segment S1 by more than a threshold level. In this example, the mean acceleration of all of the vehicles travelling in segment S1 (including vehicles that are not shown) is 0 mph with a standard deviation of 0.5 mph. It can be seen that the first and second vehicles do not deviate more than a threshold level of two standard deviations from the mean acceleration and so the behaviour of these vehicles may be classed as normal. The third vehicle, however, is decelerating sharply and has an acceleration outside of two standard deviations of the mean value. The behaviour of the third vehicle V3 does therefore deviate from the statistical profile of the road segment by more than the threshold level. The excessive speed of the third vehicle V3 may also be considered when determining whether the vehicle is operating outside of the profile.

The system may send a warning to the driver of the third vehicle V3. Alternatively, the apparatus may warn all of the drivers of the vehicles on the first segment S1 that a vehicle on the road segment is braking sharply. The warning may be conveyed to each devices within each vehicle individually or be displayed on the southbound information display 11.

The fourth vehicle V4 is not warned of the behaviour of the third vehicle because the apparatus has identified that the fourth vehicle is on the northbound carriageway segment S2 and will not be affected, for the most part, by the flow of traffic on the southbound carriageway.

The sixth, seventh and eighth vehicles V6-V8 are all in the urban road segment S6, The leading eighth vehicle V8 is pulling over and braking. The vehicle monitoring apparatus may use the contextual information that the road segment is an urban road segment S6 in determining the threshold to be applied when determining whether the accelerometer data from the vehicles V8 in the one or more road segments deviate from a statistical profile for traffic on the urban road segment S6. In this case the apparatus may send an alert to the sixth and seventh vehicle V6, V7 to be displayed on the dashboards of those vehicles to warn them of the braking eighth vehicle V8 ahead. Depending on the distance between the seventh and eighth vehicles V7, V8, the apparatus may directly control the brakes of the seventh vehicle V7 in order to prevent a collision with the eighth vehicle V8.

Claims

Claims 1. An automated method for monitoring vehicle behaviour, comprising: receiving accelerometer data and corresponding location data from a plurality of vehicles; for each vehicle, associating the accelerometer data with a road segment based on the corresponding location data; determining a profile of accelerometer data for one or more road segments; determining if accelerometer data from one or more vehicles in the one or more road segments deviate from the profile by more than a threshold level.
2. The method of claim 1 in which the accelerometer data comprise one or more of: vehicle braking, vehicle forward acceleration, vehicle lateral acceleration, and vehicle vertical acceleration.
3. The method of claim 1 further including generating an alert if the accelerometer data from the one or more vehicles deviates from the profile by more than the threshold level.
4. The method of claim 1 further including generating a vehicle use profile by aggregating said deviations from the profile for a particular vehicle.
5. The method of claim 1 further including applying a control function to a particular vehicle in the event that the accelerometer data of the particular vehicle deviate from the profile by more than the threshold level.
6. The method of claim 4 further including applying a control function to the particular vehicle if the aggregated deviations exceed a predetermined control envelope.
7. The method of claim 1 further including applying a control function to an item of traffic infrastructure in the event that the accelerometer data deviate from the profile by more than the threshold level.
8. The method of claim 1 wherein the profile comprises accelerometer data from a single other vehicle.
9. The method of claim 1 wherein the threshold is determined in accordance with a known property of the road.
10. A vehicle monitoring apparatus comprising: a database of accelerometer data profiles in which each profile is associated with one or more road segments; one or more receiver units configured to receive a vehicle position and a vehicle acceleration along at least one axis associated with a vehicle; a processor configured to determine a particular road segment associated with the vehicle based on the vehicle position and further configured to determine whether the vehicle acceleration deviates from a profile in the database associated with the particular road segment by more than a threshold level; and an alert generator configured to generate an alert in the event of a said deviation in vehicle acceleration.
11. The vehicle monitoring apparatus of claim 10 further comprising: a position determining unit configured to determine a position of the vehicle; and an accelerometer configured to determine vehicle acceleration along at least one axis.
12. The vehicle monitoring apparatus of claim 10 wherein the one or more receiver units are configured to receive a vehicle position and a vehicle acceleration along at least one axis from a plurality of vehicles, and comprising a database generator configured to generate the database of accelerometer data based on the vehicle positions and vehicle accelerations received form the plurality of vehicles.
13. A portable device for use in a vehicle comprising: a position determining unit configured to determine a vehicle position; and an accelerometer configured to determine vehicle acceleration along at least one axis; a transmitter configured to transmit the vehicle position and vehicle acceleration to a vehicle monitoring apparatus; and an alert receiver configured to receive the alert from the vehicle monitoring apparatus.
14. The portable device of claim 13 further including a control module configured to apply a control function to the vehicle in response to an alert from the alert generator.
15. A computer program configured to perform the method of one of claims 1 to 9.
16. A method substantially as described herein with reference to the accompanying 5 drawings.
17. A vehicle monitoring apparatus or portable device substantially as described herein with reference to the accompanying drawings.