Road monitoring method and system

Abstract

A method 20 and system 10 monitor road condition, by providing, for portions ( 14.1 - 14 .m) of a road 12, an approximation 210 of a roughness figure in accordance with a roughness index. The method 10 includes receiving speed data 208 of a first vehicle 16 travelling along each of the portions of the road 12 and receiving, from a measuring device 18 carried on the first vehicle 16, measured acceleration data 204 of the device 18 perpendicular to the road 12 surface. The acceleration data 204 is processed to provide a parameter value 206 relating to the acceleration data 204 for each of the portions of the road 12. A first speed-based conversion equation and the speed data 208 is utilized to convert the parameter 206 into the approximation 210 of a roughness figure for each of the portions of the road 12, in accordance with the roughness index.

1 - 27 . (canceled) 
     
     
         28 . A method for providing, for a portion of a road, an approximation of a roughness figure in accordance with a roughness index, the method comprising:
 receiving speed data of a first vehicle travelling along the portion of the road and receiving, from a measuring device carried on the first vehicle, measured acceleration data of the device perpendicular to the road surface, the first vehicle belonging to a first class of a plurality of defined different classes of vehicles, the first class of vehicles being associated with a first set of speed-based conversion equations wherein each of the speed-based conversion equations in the first set relates to a different speed, and each of the other classes of the plurality of defined different classes of vehicles being associated with a respective corresponding set of speed-based conversion equations;   processing the acceleration data, to provide a value for a parameter relating to the acceleration data for the portion of the road, the parameter being a dimensionless statistical parameter obtained by processing the z-axis acceleration data statistically; and   utilizing a first speed-based conversion equation, which is selected based on the speed data from the first set of speed-based conversion equations, to convert said parameter value into the approximation of the roughness figure for the portion of the road in accordance with the roughness index, so that data received from vehicles belonging to the different classes of vehicles traveling along the portion of the road, or vehicles travelling at different speeds along the portion of the road are comparable.   
     
     
         29 . A method according to  claim 28 , wherein the dimensionless statistical parameter is a Coefficient of Variation (CoV) which is defined as a ratio between the standard deviation (σ) and the mean (μ) of the acceleration data received for the portion of the road. 
     
     
         30 . A method according to  claim 28 , wherein each speed-based conversion equation of the first set is pre-derived by:
 utilizing a measured roughness profile in accordance with the roughness index of a reference road section having varying roughness and comprising a plurality of adjacent reference portions, to obtain an actual roughness figure for each reference portion;   obtaining acceleration data perpendicular to the road section from a first reference measuring device mounted on a first reference vehicle, having been driven along the reference road section at a respective one of the different predetermined speeds, and determining a reference parameter value relating to the acceleration data for each adjacent portion of the reference road section; and   deriving a relationship between the reference parameter values and the actual roughness figures for all the reference portions.   
     
     
         31 . A method according to  claim 28 , wherein the first set of conversion equations is loaded onto a memory arrangement of the measuring device and wherein a local controller of the measuring device selects the first speed-based conversion equation from the first set of conversion equations and converts the parameter value into the approximation of the roughness figure in accordance with the roughness index. 
     
     
         32 . A method according to  claim 28 , wherein the plurality of classes of vehicles includes at least some of: small hatchbacks, medium hatchbacks, small sedans, medium sedans, sports utility vehicles (SUVs), minibuses, and pick-up trucks. 
     
     
         33 . A method according to  claim 28 , wherein the measuring device is mounted fast on the vehicle, so that it moves in sympathy with the vehicle. 
     
     
         34 . A method according to  claim 28 , wherein the measuring device is a vehicle telematics device concealed by a body of the vehicle and comprising a three-axis accelerometer, three-axis gyroscope, Global Positioning System (GPS) that measures latitude, longitude and speed data of the telematics device, a local processor with an associated memory arrangement and a radio frequency (RF) transceiver enabling wireless data communications between the device and a central backend. 
     
     
         35 . A method according to  claim 34 , wherein the acceleration data and speed data are transmitted periodically via the transceiver to the central backend, to be processed. 
     
     
         36 . A method according to  claim 28 , wherein the roughness index is one of International Roughness Index (IRI) and Half Car Index (HRI). 
     
     
         37 . A method according to  claim 34 , wherein the local processor of the telematics device is utilized to process the acceleration data to provide the parameter value, and wherein parameter values of adjacent portions are transmitted periodically via the RF transceiver to the central backend to be converted into the approximation of the roughness figure in accordance with the roughness index. 
     
     
         38 . A method according to  claim 28 , wherein the approximated roughness figures of adjacent portions of the road section are combined to generate an approximated roughness profile of the road section in accordance with the roughness index. 
     
     
         39 . A method according to  claim 38 , wherein the approximated roughness profile is distributed to a user in the form of a visual representation. 
     
     
         40 . A method according to  claim 39 , wherein the visual representation comprises a map representing road roughness in accordance with a predetermined key. 
     
     
         41 . A method according to  claim 28 , wherein the length of the portion of the road is from 1 m to 100 m. 
     
     
         42 . A system for providing, for a portion of a road, an approximation of a roughness figure in accordance with a roughness index, the system comprising:
 a central backend;   a fleet of vehicles comprising a first class of vehicles and other classes of vehicles, the first class of vehicles comprising at least a first vehicle;   at least the first vehicle comprising: a measuring device configured to measure acceleration data perpendicular to the portion of the road; and a radio frequency (RF) transmitting device configured to communicate with the central backend;   a memory arrangement comprising at least a first set of speed-based conversion equations associated with the first class of vehicles wherein each speed-based conversion equation in the first set relates to a different speed; and a respective corresponding set of speed-based conversion equations associated with each of the other classes of vehicles;   a processor arrangement configured to: process the acceleration data measured by the measuring device into a value for a parameter: receive speed data of the first vehicle travelling along the portion of the road and to select a first speed-based conversion equation from the first set of speed-based conversion equations based on the speed-data; and utilize the first speed-based conversion equation to convert the parameter value into the approximation of the roughness figure for the portion of the road in accordance with the roughness index, wherein the parameter is a dimensionless statistical parameter obtained by processing the z-axis acceleration data statistically, so that data received from vehicles belonging to the different classes of vehicles traveling along the portion of the road, or vehicles travelling at different speeds along the portion of the road are comparable.   
     
     
         43 . A system according to  claim 42  wherein the dimensionless statistical parameter is a Coefficient of Variation (CoV) which is defined as a ratio between the standard deviation (σ) and the mean (μ) of the acceleration data received for the portion of the road. 
     
     
         44 . A system according to  claim 42 , wherein the measuring device is a vehicle telematics device. 
     
     
         45 . A system according to  claim 42 , wherein the backend comprises the memory arrangement. 
     
     
         46 . A non-transitory computer readable medium with a computer program having a program code for performing the method of  claim 28  when the program runs on a processor. 
     
     
         47 . A non-transitory computer readable medium having stored thereon data relating to at least a first pre-derived speed-based conversion equation for use by a computer program running on a processor to perform the method of  claim 28 .