SE538347C2

SE538347C2 - A system and method for identifying road surface anomalies

Info

Publication number: SE538347C2
Application number: SE1451082A
Authority: SE
Inventors: Goran Spiric; Joel Huselius
Original assignee: Scania Cv Ab
Priority date: 2014-09-16
Filing date: 2014-09-16
Publication date: 2016-05-24
Also published as: DE102015010576A1; BR102015020758A2; SE1451082A1

Abstract

Abstract The invention relates to a vehicle-mountable system (200) for identifying road surface anomalies, comprising a detection unit (210) arranged to detect at least one vehicle event based on data from at least one accelerometer (230a) on the vehicle (100). The detection unit (210) is arranged to categorize the de- tected vehicle event based on continuously received dynamic vehicle characteristics and a classification unit (220) is arranged to classify a road surface anomaly based on at least one categorized event and static vehicle characteristics. The invention also relates to a method for identifying road surface anomalies and a vehicle (100) comprising a system for identifying road surface anomalies (200).

Description

538 347 A system and method for identifying road surface anomalies TECHNICAL FIELD The present invention relates to a system for identifying road surface anoma- lies, a method for identifying road surface anomalies and a vehicle comprising such a system.

BACKGROUND A vehicle is in several ways affected by the quality of the road on which the vehicle is traveling. Unevenness on the road surface, such as potholes, bumps, pavements, railway tracks and other defects or anomalies may affect the vehicle life, the fuel consumption of the vehicle and the comfort of the vehi- cle passengers. It is therefore desirable to gather information about such anomalies so that the operator of the vehicle can avoid them. Different methods and systems for detection of road anomalies exist, where sensors such as accelerometers or optical sensors arranged on the vehicle detect anomalies on the road surface.

Document US 2014/0122014 Al discloses a method for detecting road unevenness by reading in a plurality of records that each have at least one geographical position and one information item allocated to this geographic position about a detected local unevenness of the road surface. The records are provided by different vehicles and this way, errors or uncertainties which occur during the detection of individually detected unevennesses of the road surface at the geographical position are compensated for by a statistical evaluation. The information about the local unevenness can be acquired by a sensor on a vehicle.

Document US 2009/0164063 Al discloses a vehicle-mounted system for monitoring road surface defects comprising detectors, such as shock detectors, 1 538 347 which may provide information about the size and depth of detected bumps. A positioning system determines the instant location of the vehicle and a repository stores a location of the surface defect with reference to the instant location. The system further comprises a controller unit which identifies an immi- nent defect encounter and determines guidance instructions to minimize the effect of the defect encounter.

Methods and systems for detecting and avoiding road surface anomalies in various ways are thus commonly known and the anomalies may be classified based on the size/depth of the anomaly. However, known solutions are vehicle specific and do not consider the fact that road surface anomalies are perceived differently by different types of vehicles and different types of vehicles are thereby also affected in different ways by the same road surface anomaly. Thus, despite known solutions in the field, there is still a need to develop a system and a method for identifying road surface anomalies, which is flexible and suitable for any type of vehicle.

SUMMARY OF THE INVENTION An object of the present invention is to achieve a system for identifying road surface anomalies, which minimises the risk for vehicle damages and accidents.

Another object of the invention is to achieve a system for identifying road sur- face anomalies, which minimises the fuel consumption of the vehicle.

A further object of the invention is to achieve a system for identifying road sur- face anomalies, which increases the comfort of the vehicle passengers.

Another object of the invention is to achieve a system for identifying road sur- face anomalies, which is flexible and suitable for all types of vehicles. 2 538 347 Another object of the present invention is to achieve a system for identifying road surface anomalies, which detects and classifies road surface anomalies in an accurate way.

A further object of the present invention is to achieve a system for identifying road surface anomalies, which is reliable and efficient.

Another object of the present invention is to achieve a method for identifying road surface anomalies, which minimises the risk for vehicle damages and ac- cidents.

Another object of the invention is to achieve a method for identifying road surface anomalies, which minimises the fuel consumption of the vehicle.

A further object of the invention is to achieve a method for identifying road sur- face anomalies, which increases the comfort of the vehicle passengers.

Another object of the present invention is to achieve a method for identifying road surface anomalies, which is flexible and suitable for all types of vehicles.

Another object of the present invention is to achieve a method for identifying road surface anomalies, which detects and classifies road surface anomalies in an accurate way.

A further object of the present invention is to achieve a method for identifying road surface anomalies, which is reliable and efficient.

The herein mentioned objects are achieved by a system according to claim 1 and a method according to claim 14.

According to an aspect of the present invention a vehicle-mountable system for identifying road surface anomalies is provided, comprising a detection unit 3 538 347 arranged to detect at least one vehicle event based on data from at least one accelerometer on the vehicle. The detection unit is arranged to categorize the detected vehicle event based on continuously received dynamic vehicle characteristics and a classification unit is arranged to classify a road surface anomaly based on at least one categorized event and static vehicle character- istics.

A road surface anomaly may for example be a bump, a pothole, a railway track, a pavement, defects or other unevennesses on the road surface. The road sur- face anomaly may be a fixed anomaly or a moving anomaly, such as an animal or an object lying on the road.

The accelerometer on the vehicle continuously registers acceleration data in three dimensions and continuously transfers the data to the road analysis sys- tern. How many accelerometers a vehicle has, and where they are arranged, depend for example on the type of vehicle, the frame properties of the vehicle and the suspension properties of the vehicle. When the vehicle encounters a road surface anomaly the accelerometers are affected and the acceleration data transferred to the detection unit from the accelerometer indicates that something has happened to the vehicle. Thus, the detection unit detects a ve- hicle event based on the acceleration data from the accelerometers, which, in turn, indicates that the vehicle might have encountered a road surface anomaly. By categorizing the vehicle event based on continuously received dynamic vehicle characteristics the system can accurately evaluate the vehicle event.

The classification unit receives information on the categorized vehicle event and static vehicle characteristics, assesses the vehicle event, and classifies a road surface anomaly causing the vehicle event based on this information. This way, the system is adaptable and takes into account the differences between different vehicles and the fact that different vehicles perceive road sur- face anomalies in different ways and also are affected by road surface anoma- lies in different ways. A flexible system, which is suitable for and may be implemented in all types of vehicles, is thereby achieved. 4 538 347 The classified road surface anomaly is preferably registered and saved in the system for identifying road surface anomalies. This way, the next time the vehicle travels in the same geographic location, the operator may be notified about the road surface anomaly. The operator may then adapt the driving in order to avoid the anomaly or to minimise the effect of the anomaly. A system for identifying road surface anomalies, which minimises the risk for vehicle damages and increases the comfort of the passengers is thereby achieved.

According to an aspect of the invention the detection unit is arranged to cate- gorize the at least one vehicle event by where on the vehicle it was detected, the time of the vehicle event, geographic location of the vehicle and the severity of the event. The dynamic vehicle characteristics are preferably transferred to the detection unit from one or several internal vehicle systems and/or sensors. Where on the vehicle the event was detected is preferably categorized by right or left and front or rear. The geographic location of the vehicle at the mo- ment of detection of a vehicle event is provided by a navigation system, such as a GPS, Galileo or similar, arranged in communication with the detection unit. The severity of the vehicle event is suitably indicated by a severity measure, for example a number between 1-10 where 1 is low severity and 10 high se- verity. By severity is meant the impact the vehicle event has on the vehicle.

The severity of the vehicle event is preferably determined based on the accelerometer data adapted to current circumstances given by the dynamic vehicle characteristics According to an aspect of the invention the dynamic vehicle characteristics comprise an estimated weight of the vehicle. The weight of the vehicle influences the way the vehicle and the accelerometer reacts on a road surface anomaly. By estimating the weight of the vehicle the detection unit can thereby assess the accelerometer data in a more accurate way. This way, a reliable categorisation of the vehicle event is provided and thus a reliable classification of the road surface anomaly causing the vehicle event. Specifically, the esti- 538 347 mated weight of the vehicle is considered by the detection unit when determining the severity of the vehicle event.

According to an aspect of the invention the dynamic vehicle characteristics comprise the current gear selection. A change of gear may cause the vehicle to jerk which may affect the accelerometers in the vehicle. By considering the current gear selection the detection unit can determine if a change of gear has occurred and thus assess if the indication of a vehicle event from the accelerometers was caused by a change of gear, a road surface anomaly or both.

This way, a reliable categorisation of the vehicle event is provided.

According to an aspect of the invention the dynamic vehicle characteristics comprise the current brake force. A sudden deceleration of the vehicle may affect the accelerometers in the vehicle. By considering the current brake force the detection unit can determine if the indication of a vehicle event from the accelerometers was caused by a sudden braking, a road surface anomaly or both.

By considering the current gear selection and/or the current brake force, the detection unit can also determine if the operator of the vehicle has adapted the driving after the current road conditions. The reason for the operator of the vehicle to shift gear and increase the brake force could be that the operator has distinguished a road surface anomaly down the road and thus adapts the vehicle speed in order to minimise the effect of the anomaly on the vehicle. By considering this information when the detection unit detects a vehicle event, the detection unit can better assess the actual severity of the road surface anomaly.

According to an aspect of the invention the dynamic vehicle characteristics comprise the current vehicle speed. The speed of the vehicle influences the way the vehicle and the accelerometer reacts on a road surface anomaly. A vehicle travelling over a bump with a high speed will for example cause a great 6 538 347 reaction on the accelerometers while a vehicle travelling over a bump with a low speed will result in a smaller reaction. By estimating the speed of the vehicle the detection unit can assess the accelerometer data in a more accurate way and thereby categorize the vehicle event more accurately.

The dynamic vehicle characteristics may comprise the current steering angle in order to determine if the vehicle event is detected while the operator is turning the vehicle. This might indicate that the operator is steering away from a road surface anomaly and that the anomaly thus in fact is more severe than indi- cated by the accelerometers. The steering angle is thus useful in order for the detection unit to accurately categorize the vehicle event. If the vehicle is turning while a vehicle event is detected, there is also a possibility that another accelerometer on the vehicle would have been affected if the vehicle wouldn't have turned. The steering angle may thus by useful when classifying the road surface anomaly and determining the type of road surface anomaly.

According to an aspect of the invention the static vehicle characteristics comprise suspension properties and/or wheel configuration and/or frame properties and/or vehicle type. The suspension properties, the wheel configuration, the frame properties and the type of vehicle influence how the vehicle reacts on a road surface anomaly. By considering such static vehicle characteristics an accurate and reliable classification of a road surface anomaly may be provided by the classification unit.

The static vehicle characteristics are preferably communicated to the system for identifying road surface anomalies from an internal vehicle system. Alternatively, the static vehicle characteristics are communicated to the system for identifying road surface anomalies from a plurality of internal vehicle systems.

According to an aspect of the invention the system for identifying road surface anomalies is configured with algorithm parameters, such as acceleration filter and/or weight adjustment parameters and/or location of accelerometer meas- 7 538 347 urement points and/or acceleration parameters. The acceleration parameters are preferably vertical, lateral and longitudinal. The algorithm parameters are preferably set such as to achieve an accurate and desirable classification of a road surface anomaly.

According to an aspect of the invention the classification unit is configured with a temporal hysteresis for a required duration of a detected vehicle event. The classification unit is suitably arranged to classify the road surface anomaly based on the temporal hysteresis for a required duration of a detected event.

The classification unit receives information about the categorized vehicle event detected and categorized by the detection unit and can thus determine the duration of the detected vehicle event. The temporal hysteresis is preferably set such that a vehicle event which lasts a very short period of time, for example less than 25 milliseconds, is determined not to have been caused by a road surface anomaly and no classified road surface anomaly is registered in the system. The temporal hysteresis is preferably set such that in order to determine that a vehicle event has been caused by a road surface anomaly, the vehicle event must have lasted longer than 25 milliseconds. Alternatively, the temporal hysteresis may be set such that the required minimum duration of a detected vehicle event is between 20-30 milliseconds. The required duration of a detected vehicle event is preferably determined based on the vehicle speed and a predetermined minimum length of a road surface anomaly. By configuring the system with the temporal hysteresis for a required duration of a detected event, classification and registration of too many anomalies may be avoided. The temporal hysteresis also means that small and insignificant anomalies with essentially no impact on the vehicle are not classified and registered unnecessarily.

According to an aspect of the invention the classification unit is configured with a temporal hysteresis for a minimum time between detected vehicle events.

The classification unit is arranged to classify the road surface anomaly based on the temporal hysteresis for a minimum time between detected vehicle 8 538 347 events. When a vehicle encounters a road surface anomaly typically the left and/or right front wheels passes the anomaly first, and subsequently the rear left and/or right wheels. If each wheel is associated with an accelerometer this would result in at least four different detected events, each categorized after the time of detection, geographic location of the vehicle, severity and position on the vehicle. In order to avoid classifying and registering four different road surface anomalies, one per each vehicle event, a temporal hysteresis for a minimum time between detected events is set in the system. The temporal hysteresis is preferably set such that at least 0,1 seconds must have passed between two detected vehicle events, or the two vehicle events are considered to have been caused by the same road surface anomaly. Alternatively, the temporal hysteresis is set such that the minimum time between detected vehicle events is between 0,05-0,15 seconds. This way, the four detected vehicle events in the example are considered to have been caused by the same road surface anomaly and only one road surface anomaly is classified and regis- tered. The minimum time between detected vehicle events is preferably determined based on the length of the vehicle and the vehicle speed.

Preferably, the identified anomaly is classified by geographic location, type and severity. The type of an anomaly may for example be described as the shape and/or extension of the anomaly, such as a longitudinal anomaly extending across the width of the traffic lane, an anomaly on one side of the traffic lane, an anomaly extending diagonally across the traffic lane or similar. The type could also be a pothole, a bump, a railway track etc. The severity is a measure of how the vehicle is affected by the road surface anomaly. The severity of the road surface anomaly may differ from the severity of the vehicle event as determined in the categorization. In cases where several accelerometers on a vehicle each detect a vehicle event, each vehicle event is categorized independently. This may result in different severity measures for each vehicle event, even though they are all caused by the same road surface anomaly.

When the classification unit determines that several vehicle events are caused by the same road surface anomaly, the anomaly is classified with a severity 9 538 347 which is a combination of the different severity measures of the vehicle events. The classification of the road surface anomaly is registered in the system and may be used in order to warn the operator of the vehicle the next time he travels on the same geographic location. By classifying the road surface anoma- lies by geographic location, type and severity the operator of the vehicle has plenty of information and can thereby take accurate action in order to avoid the anomaly or adapt the driving such that the effect of the anomaly on the vehicle is minimised. The notification of a classified road surface anomaly is preferably communicated to a display device in the vehicle.

According to an aspect of the invention the road surface anomaly is classified by a probability measure. The classification unit preferably assesses how likely it is that a road surface anomaly caused the detected vehicle event and thus determines a probability measure. The probability measure is preferably de- termined based on the categorized vehicle event and dynamic vehicle charac- teristics, such as vehicle speed, brake force and gear selection, communicated to the classification unit from the detection unit.

The classification unit, and thus the system for identifying road surface anoma- lies, is preferably arranged to transfer information about the classified road sur- face anomaly to a vehicle external system. Alternatively, the system is arranged to transfer the information about the classified road surface anomaly to other vehicles.

According to an aspect of the invention a method for identifying road surface anomalies is provided, comprising the step to: -detect at least one vehicle event, by means of a detection unit, based on data from at least one accelerometer on the vehicle. The method further comprises the steps to: - categorize the at least one detected vehicle event based on continuously re- ceived dynamic vehicle characteristics; and 538 347 - classify a road surface anomaly, by means of a classification unit, based on the categorized event and static vehicle characteristics.

The detection unit suitably categorizes the at least one vehicle event by where on the vehicle it was detected, the time of the event, geographic location of the vehicle and the severity of the event.

According to an aspect of the invention the dynamic vehicle characteristics comprise an estimated weight of the vehicle and/or the current gear selection and/or the current brake force and/or the current vehicle speed.

According to an aspect of the invention the static vehicle characteristics comprise suspension properties and/or wheel configuration and/or frame properties and/or vehicle type.

The classification unit preferably classifies the road surface anomaly by geographic location, type and severity. The classification unit may classify the road surface anomaly by a probability measure.

The classification unit suitably classifies the road surface anomaly based on a temporal hysteresis for a required duration of a detected vehicle event. The classification unit suitably classifies the road surface anomaly based on a temporal hysteresis for a minimum time between detected vehicle events.

According to an aspect of the invention, the method comprises the step to - transfer the classification of the road surface anomaly from the classification unit to a vehicle external system.

The herein mentioned objects are also achieved by a motor vehicle comprising a road analysis system. The vehicle may be a truck, a bus, a mining vehicle, a wheel loader, a car or similar. 11 538 347 According to an aspect of the invention, a computer program is provided, wherein said computer program comprises programme code for causing an electronic control unit or another computer connected to the electronic control unit to perform the steps according to any of the claims 14-17.

According to an aspect of the invention a computer programme product is provided, comprising a programme code stored on a computer-readable medium for performing the method steps according to any of claims 14-17 , when said computer programme is run on an electronic control unit or another computer connected to the electronic control unit.

Further objects, advantages and novel features of the present invention will become apparent to one skilled in the art from the following details, and also by putting the invention into practice. Whereas the invention is described be- low, it should be noted that it is not restricted to the specific details described.

Specialists having access to the teachings herein will recognise further applications, modifications and incorporations within other fields, which are within the scope of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS For fuller understanding of the present invention and further objects and advantages of it, the detailed description set out below should be read together with the accompanying drawings, in which the same reference notations de- note similar items in the various diagrams, and in which: Figure 1schematically illustrates a vehicle according to an embodiment of the invention; Figure 2schematically illustrates a road analysis system according to an embodiment of the invention; Figure 3illustrates a flow chart for a method for analysing a road according to an embodiment of the invention; and 12 538 347 Figure 4schematically illustrates a computer according to an embodiment of the invention.

DETAILED DESCRIPTION OF THE DRAWINGS The term "link" refers herein to a communication link which may be a physical connection such as an opto-electronic communication line, or a non-physical connection such as a wireless connection, e.g. a radio link or microwave link.

Figure 1 shows a side view of a vehicle 100 comprising a vehicle-mountable system 200 for identifying road surface anomalies according to an embodiment of the invention. The exemplified vehicle 100 comprises a tractor unit 1 and a trailer 112. The vehicle may be a heavy vehicle, e.g. a truck or a bus.

The vehicle may alternatively be a passenger car. The vehicle may be a hybrid vehicle, an electrical vehicle or a vehicle driven by a combustion engine.

Figure 2 shows a vehicle-mountable system 200 for identifying road surface anomalies according to an embodiment of the invention. The system 200 comprises a detection unit 210 and a classification unit 220.

The detection unit 210 is arranged to identify a road surface anomaly by detecting a vehicle event. A vehicle event is detected by means of at least one accelerometer 230a or similar sensor devices arranged on the vehicle 100 in communication with the detection unit 210. Preferably, a plurality of accelerometers 230a is arranged on the vehicle 100. The accelerometers communicate with the detection unit 210 and thus the system 200 through a link L230a. The accelerometers 230a communicate acceleration data in three dimensions, which acceleration data is affected by road surface anomalies. The detection unit 210 can thereby detect that something has happened to the vehicle 100, a 13 538 347 vehicle event, by analysing the acceleration data from the accelerometers 230a.

The detection unit 210 is also arranged to categorize the detected vehicle events based on continuously received dynamic vehicle characteristics. The dynamic vehicle characteristics might be communicated to the detection unit 210 from at least one internal vehicle system 230b, 230c, via a link L230b, L230c. Only two vehicle internal systems 230b, 230c are shown in the figure but the invention is however not limited to this. There could be any number of internal vehicle systems 230b, 230c transferring dynamic vehicle characteristics to the detection unit 210. The dynamic vehicle characteristics may be the time of the vehicle event and/or vehicle speed and/or weight estimation of the vehicle and/or the current gear selection and/or the current brake force and/or steering wheel angle and/or geographic location. The geographic location is suitably provided by a navigation system such as a GPS or similar. By consid- ering such dynamic vehicle characteristics, the detection unit 210 categorizes the vehicle event by time of the event, the geographic location of the vehicle 100 during the detection of the vehicle event, where on the vehicle 100 the vehicle event was detected and the severity of the vehicle event. The position on the vehicle 100 where the event is detected is preferably categorized by right or left and front or rear. The severity of the vehicle event is suitably indicated by a severity measure, for example a number between 1-10 where 1 is low severity and 10 high severity. By severity is meant the impact the vehicle event, and thus the road surface anomaly, has on the vehicle 100. The sever- ity of the vehicle event is preferably determined based on the accelerometer data adapted to current circumstances given by the dynamic vehicle characteristics.

The categorization of the vehicle events is communicated via a link L210 from 30 the detection unit 210 to the classification unit 220. The classification unit 220 is arranged to classify a road surface, based on the categorized vehicle event and static vehicle characteristics. The static vehicle characteristics are pref- 14 538 347 erably provided from one or a plurality of internal vehicle systems 240 via a link L240 to the classification unit 220. The static vehicle characteristics may be suspension properties of the vehicle 100 and/or wheel configuration of the vehicle 100 and/or vehicle type and/or frame properties of the vehicle 100. Type of vehicle may be such as a truck, a bus or a car.

The system for identifying road surface anomalies 200 is configured with algorithm parameters, such as an acceleration filter and/or weight adjustment parameters and/or location of accelerometer measurement points and/or accel- eration parameters. These algorithm parameters are set in order to achieve an accurate classification of the road surface anomaly.

The classification unit 220 is configured with a temporal hysteresis for a required duration of a detected event. The classification unit 220 is arranged to classify the identified road surface anomaly based on the temporal hysteresis for a required duration of a detected event. The classification unit 220 determines the duration of the detected vehicle event based on the information about the categorized vehicle event detected and categorized by the detection unit 210. The temporal hysteresis is preferably set such that a vehicle event which lasts a very short period of time, for example less than 25 milliseconds, is determined not to have been caused by a road surface anomaly and no classified road surface anomaly is registered in the system 200. The temporal hysteresis is preferably set such that in order to determine that a vehicle event has been caused by a road surface anomaly, the vehicle event must have lasted longer than 25 milliseconds. Alternatively, the temporal hysteresis may be set such that the required minimum duration of a detected vehicle event is between 20-30 milliseconds.

The classification unit 220 is further configured with a temporal hysteresis for a minimum time between detected events. The classification unit 220 is arranged to classify the identified road surface anomaly based on the temporal hysteresis for a minimum time between detected events. If the vehicle 100 has for ex- 538 347 ample four accelerometers 230a and encounters a road surface anomaly, each accelerometer 230a might be affected by the anomaly. The detection unit 210 thus detects four vehicle events within a short period of time. Each detected vehicle event is categorized after the time of detection, geographic loca- tion of the vehicle, severity and position on the vehicle 100. In order to avoid classifying and registering four different road surface anomalies, one per each vehicle event, a temporal hysteresis for a minimum time between detected events is set in the road analysis system. The temporal hysteresis is preferably set such that at least 0,1 seconds must have passed between two detected vehicle events, or the two vehicle events are considered to have been caused by the same road surface anomaly. Alternatively, the temporal hysteresis is set such that the minimum time between detected vehicle events is between 0,050,15 seconds. This way, the four detected vehicle events in the example are considered to have been caused by the same road surface anomaly and only one road surface anomaly is classified and registered.

The classification unit 220 classifies each road surface anomaly by geographic location, type and severity. The type of the anomaly may for example be the shape and extension of the anomaly, such as a longitudinal anomaly extending across the width of the traffic lane, an anomaly on one side of the traffic lane, an anomaly extending diagonally across the traffic lane or similar. The type could also be one of the categories pothole, bump, railway track, pavement etc. The classified severity is a measure of how the vehicle 100 is affected by the road surface anomaly. When the classification unit 220 determines that several vehicle events are caused by the same road surface anomaly, the anomaly is classified with a severity which is a combination of the different severity measures of the vehicle events. The identified anomaly is also classified by a probability measure. The classification unit 220 preferably assesses how likely it is that it actually is a road surface anomaly that caused the detected vehicle event and thus determines a probability measure. The probability measure is preferably determined based on the categorized vehicle event and dynamic 16 538 347 vehicle characteristics such as vehicle speed, brake force and gear selection communicated from the detection unit 210 via link L210.

The classified road surface anomaly is registered and saved in the system 200 and may be used in order to warn the operator of the vehicle 100 the next time he travels on the same geographic location. The operator may be warned by a visual warning, a haptic warning and/or an acoustic warning by means of a warning unit. The classified road surface anomaly may also be communicated to one or several vehicle external systems 250 via a link L220.

Figure 3 shows a flowchart for a method for identifying road surface anomalies according to an embodiment of the invention. The method comprises the step to detect s302, by means of detection unit 210, at least one vehicle event based on data from at least one accelerometer 230a on the vehicle. The method further comprises the step to categorize s304 the at least one detected vehicle event based on continuously received dynamic vehicle characteristics and the step to classify s306 a road surface anomaly, by means of a classification unit 220, based on the categorized vehicle event and static vehicle characteristics.

Acceleration data from the at least one accelerometer 230a is communicated to the detection unit 210 via a link L230a. The dynamic vehicle characteristics are preferably provided by one or a plurality of internal vehicle systems 230b, 230c. The dynamic vehicle characteristics are suitably communicated to the detection unit 210 via links L230b, L230c.

The detection unit 210 suitably categorizes the at least one vehicle event by where on the vehicle 100 it was detected, the time of the vehicle event, geographic location of the vehicle 100 when the vehicle event was detected and the severity of the vehicle event. The categorized vehicle event is communi- cated to the classification unit 220 via a link L210. 17 538 347 The dynamic vehicle characteristics preferably comprise an estimated weight of the vehicle 100 and/or the current gear selection and/or the current brake force and/or the current vehicle speed.

The static vehicle characteristics preferably comprise suspension properties and/or wheel configuration and/or frame properties and/or vehicle type. The static vehicle characteristics are preferably provided by at least one internal vehicle systems 240. The static vehicle characteristics are communicated from the internal vehicle system 240 to the classification unit 220 via a link L240.

The classification unit 220 classifies the road surface anomaly based on a temporal hysteresis for a required duration of a detected event. The classification unit 220 determines the duration of the detected vehicle event based on the information about the categorized vehicle event detected and categorized by the detection unit 210. The classification unit 220 further determines, based on the temporal hysteresis, if the vehicle event lasted long enough to be considered to have been caused by a road surface anomaly. The classification unit 220 also classifies the road surface anomaly based on a temporal hysteresis for a minimum time between detected events. The classification unit 220 thus determines if a plurality of vehicle events detected within a short period of time are caused by one and the same road surface anomaly or if a plurality of road surface anomalies should be classified and registered.

The classification unit 220 preferably classifies the road surface anomaly by geographic location, type and severity. The classification unit 220 may also classify the road surface anomaly by a probability measure.

According to an aspect of the invention, the method comprises the step to transfer the classified road surface anomaly from the classification unit 220 to a vehicle external system 250. The classified road surface anomaly is prefera- bly communicated to the vehicle external system 250 via a link L220. 18 538 347 Figure 4 is a diagram of a version of a device 400. The system 200, detection unit 210 and/or classification unit 220 described with reference to Figure 2 may in a version comprise the device 400. The device 400 comprises a non-volatile memory 420, a data processing unit 410 and a read/write memory 450. The non-volatile memory 420 has a first memory element 430 in which a computer programme, e.g. an operating system, is stored for controlling the function of the device 400. The device 400 further comprises a bus controller, a serial communication port, I/O means, an AID converter, a time and date input and transfer unit, an event counter and an interruption controller (not depicted).

The non-volatile memory 420 has also a second memory element 440.

There is provided a computer programme P which comprises routines for continuously identifying road surface anomalies, detecting at least on vehicle event, categorizing the at least one vehicle event and classifying a road sur- face anomaly. The computer programme P comprises routines for detecting a vehicle event based on acceleration data from at least on accelerometer 230a arranged on the vehicle 100. The computer programme P comprises routines for categorizing a vehicle event based on dynamic vehicle characteristics. The computer programme P comprises routines for classifying a road surface anomaly based on at least one categorized vehicle event and static vehicle characteristics.

The computer programme P comprises routines for communicating a classified road surface anomaly to a vehicle external system.

The programme P may be stored in an executable form or in a compressed form in a memory 460 and/or in a read/write memory 450.

Where the data processing unit 410 is described as performing a certain func- tion, it means that the data processing unit 410 effects a certain part of the programme stored in the memory 460 or a certain part of the programme stored in the read/write memory 450. 19 538 347 The data processing device 410 can communicate with a data port 499 via a data bus 415. The non-volatile memory 420 is intended for communication with the data processing unit 410 via a data bus 412. The separate memory 460 is intended to communicate with the data processing unit 410 via a data bus 411.

The read/write memory 450 is adapted to communicating with the data processing unit 410 via a data bus 414. The data port 499 may for example have the links L210, L220, L230a-c and L240 connected to it (see Figure 2).

When data are received on the data port 499, they are stored temporarily in the second memory element 440. When input data received have been temporarily stored, the data processing unit 410 is prepared to effect code execution as described above.

Parts of the methods herein described may be effected by the device 400 by means of the data processing unit 410 which runs the programme stored in the memory 460 or the read/write memory 450. When the device 400 runs the programme, methods herein described are executed.

The foregoing description of the preferred embodiments of the present inven- tion is provided for illustrative and descriptive purposes. It is not intended to be exhaustive or to restrict the invention to the variants described. Many modifications and variations will obviously be apparent to one skilled in the art. The embodiments have been chosen and described in order best to explain the principles of the invention and its practical applications and hence make it pos- sible for specialists to understand the invention for various embodiments and with the various modifications appropriate to the intended use.

Claims

538 347 Claims

1. A vehicle-mountable system (200) for identifying road surface anomalies, comprising a detection unit (210) arranged to detect at least one vehicle event based on data from at least one accelerometer (230a) on the vehicle (100), characterized in that the detection unit (210) is arranged to categorize the detected vehicle event based on continuously received dynamic vehicle characteristics and a classification unit (220) is arranged to classify a road surface anomaly based on at least one categorized event and static vehicle characteristics and wherein the detection unit (210) is arranged to categorize the de- 1 0tected vehicle event by where on the vehicle (100) it was detected, the time of the vehicle event, geographic location of the vehicle (100) and the severity of the vehicle event.

2. A system according to claim 1 , wherein the dynamic vehicle characteristics comprise an estimated weight of the vehicle (100).

3. A system according to any of the preceding claims, wherein the dynamic vehicle characteristics comprise the current gear selection.

4. A system according to any of the preceding claims, wherein the dynamic vehicle characteristics comprise the current brake force.

5. A system according to any of the preceding claims, wherein the dynamic vehicle characteristics comprise the current vehicle speed.

6. A system according to any of the preceding claims, wherein the static vehicle characteristics comprise suspension properties and/or wheel configuration and/or frame properties and/or vehicle type.

7. A system according to any of the preceding claims, wherein the system (200) is configured with algorithm parameters, such as acceleration filter 21 538 347 and/or weight adjustment parameters and/or location of accelerometer measurement points and/or acceleration parameters.

8. A system according to any of the preceding claims, wherein the classifica- tion unit (220) is configured with a temporal hysteresis for a required duration of a detected vehicle event.

9. A system according to any of the preceding claims, wherein the classification unit (220) is configured with a temporal hysteresis for a minimum time be- tween detected vehicle events.

10. A system according to any of the preceding claims, wherein the classification unit (220) is arranged to classify the anomaly by geographic location, type and severity.

11. A system according to any of the preceding claims, wherein the classification unit (220) is arranged to classify the anomaly by probability.

12. A system according to any of the preceding claims, wherein the system (200) is arranged to transfer the classified road surface anomaly to a vehicle external system (250).

13. A motor vehicle (100) comprising a system (200) according to any of claims 1-12.

14. A method for identifying road surface anomalies with a vehicle-mountable system for identifying road surface anomalies (200), comprising the step to: - detect (s302) at least one vehicle event, by means of a detection unit (210), based on data from at least one accelerometer (230a) on the vehicle (100), characterized by the steps to: - categorize (s304) the at least one detected vehicle event based on continuously received dynamic vehicle characteristics; and 22 538 347 - classify (s306) a road surface anomaly, by means of a classification unit (220), based on the categorized vehicle event and static vehicle characteristics and wherein the detection unit (210) categorizes the at least one vehicle event by where on the vehicle it was detected, the time of the vehicle event, geo- graphic location of the vehicle (100) and the severity of the vehicle event.

15. A method according to claim 14, wherein the dynamic vehicle characteristics comprise an estimated weight of the vehicle and/or the current gear selection and/or the current brake force and/or the current vehicle speed.

16. A method according to any of claims 14-15, wherein the static vehicle characteristics comprise suspension properties and/or wheel configuration and/or frame properties and/or vehicle type.

17. A method according to any of claims 14-16, wherein the road surface anomaly is classified by geographic location, type and severity.

18. A computer program (P), wherein said computer program comprises programme code for causing an electronic control unit (200; 210; 220; 400) or an- other computer (200; 210; 220; 400) connected to the electronic control unit (200; 210; 220; 400) to perform the steps according to any of the claims 14-17.

19. A computer programme product comprising a programme code stored on a computer-readable medium for performing the method steps according to any of claims 14-17, when said computer programme is run on an electronic con- trol unit (200; 210; 220; 400) or another computer (200; 210; 220; 400) connected to the electronic control unit (200; 210; 220; 400). 23 538 347 I foljande bilaga finns en oversattning av patentkraven till svenska. Observera att det r patentkravens lydelse pa engelska som gaiter. A Swedish translation of the patent claims is enclosed. Please note that only the English claims have legal effect.