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ROAD PROFILING-ROUGHNESS Presentation by Niranjan Santhirasegaram

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1 ROAD PROFILING-ROUGHNESS Presentation by Niranjan Santhirasegaram

2 FHWA’s Office of Pavement Technology
Introduction “ Smooth pavement makes sense from an agency and a user perspective. It’s what the public wants, and it’s what they should have.” Mark Swanlund FHWA’s Office of Pavement Technology

3 Roughness What’s ‘Roughness’? Roughness is defined as a measure of surface irregularities with wavelengths between 0.5 and 100 metre in the longitudinal profile of a traffic lane.

4 Short Wavelength Roughness Long Wavelength Roughness

5 Method of Determining Roughness
Site inspection by Estimations Mechanical (NAASRA roughness meter ) bump car Non contact profilometers which use accelerometers and height sensors (Laser)

6 NAASRA is National Association of Australian State Road Authorities
Roughness Roughness Measures International Roughness Index (IRI) NAASRA Roughness Counts (NRM) Heavy Articulated Truck Ride Index (HATI) NAASRA is National Association of Australian State Road Authorities

7 International Roughness Index (IRI) Unit of IRI is m/km or mm/m
The accumulation of suspension travel over a km of the results of the application of a computer model of a standard “quarter car” to the measured longitudinal road profile of each wheelpath. The simulated travel speed of the quarter car model is 80km/hr Unit of IRI is m/km or mm/m

8 Roughness What is IRI roughness ?
Lane IRIqc is the composite IRI value representing the roughness of a traffic lane within a section of road. It is determined by averaging two single track IRIqc values obtained separately in each wheelpath of a lane. The IRIhc is calculated by applying the IRI algorithm to the average of the wheelpath profiles

9 What is NAASRA Roughness ?
NAASRA Roughness (counts/km) is a measure of the dynamic response of a NAASRA standard passenger vehicle in response to two longitudinal profiles measured simultaneously.

10 NAASRA Roughness Counts per km (NRM)
The cumulative total relative upward displacement between axle and body of a standard car, registered in units of counts per km of distance travelled at either of two principal standard speeds. 80 km/h or 50km/h. One NAASRA count corresponds to a measured axle to body displacement of 15.2 mm (measured either up or down, but not both) Each wheelpath is analysed through the “quarter-car” model to determine the Single Track IRIqc for each wheelpath for each 100m segment.

11 Roughness IRI values are averaged and then converted by applying the following equations Lane IRIqc = (Single Track IRIqc (inner) + Single Track IRIqc (outer) )/2 Lane IRIhc = A number calculated by applying the IRI algorithm to the average of two profiles NAASRA(counts/km) = 26.49* Lane IRIqc NAASRA(counts/km) half Car = * Lane IRIhc PIL,PIR are left and right Profile Index HRI = 0.79IRI ( By Estimation)

12 Source: (Sayers and Karamihas, 1998, p. 61)
Roughness Source: (Sayers and Karamihas, 1998, p. 61)

13 Profile based measurements available in Australasia
Roughness Profile based measurements available in Australasia

14 Roughness Surveys Introduction
Network surveys to be undertaken in the lane carrying the heaviest traffic loading, following the most common wheelpaths, and reporting roughness at intervals of 100m, either in IRI (m/km) or NRM (counts/km). (The wheelpaths are deemed to be offset 0.75m from the centreline of the lane)

15 Data reporting Roughness should be recorded for each 100m segment as:
Lane roughness (IRIqc) in m/km to not more than two decimal places. Lane roughness in NAASRA Roughness Counts (counts/km) to the nearest whole number. The location of significant road features such as bridges, intersections, administrative borders, etc should be incorporated in roughness reports, to enable each 100m segment to be uniquely identified in terms of the road agency’s location system. Roughness reports should clearly identify the lane surveyed and the direction and speed of travel during the survey, as well as the date and weather conditions. Any impediment to the survey such as roadwork's, traffic congestion, localised wet surfaces , or obstacles that may cause lane change maneuvers should be noted.

16 Data reporting For each test run, the following data must be recorded:
(a) Survey title / Contract Number (b) Date and Time (c) Survey Device Identification (d) Operator (e) Driver (f) Road number / Reference (g) Road Name (if applicable) (h) Test Direction (i) Test Lane (j) Start and End References (k) Intermediate Features and/or Reference Points (if applicable) (l) Any unusual occurrences (e.g. lane changes, bridge abutments, end of seal, etc.).

17 IRI Range Represented by Different Classes of Roads
Roughness IRI Range Represented by Different Classes of Roads

18 Roughness Roughness values (NRM counts/km) for varying traffic ranges

19 Equipments to measure Roughness
ROMDAS Z-250 ARAN ARRB Walking Profilometer NAASRA Bump Car Greenwood Laser profilomete Merlin

20 The preferred configuration of laser Profilometer
Laser configuration The preferred configuration of laser Profilometer Photos source: Austroads. 2007

21 Roughness

22 Contributing Factors to Roughness
1 Water ingress Further cracking Patches Shear Uneven surface Spalling Faster deformation ROUGHNESS Potholes Time Surface Lower strength Area of Cracking Rut depth

23 Frequency and scope of Roughness surveys.

24 Roughness Roughness information can be used for one or more of three main purposes. Road network condition monitoring ( including performance measures) Project level analysis (e.g, life cycle costing, & quality assessment of new works.) Network level analysis (e.g., deterioration modeling & Forward works program) Research ( e.g, development of models, truck ride indicators.)

25 Roughness information is also used to assist in
Assessing the suitability of a road for its users. Assessing the relative condition of distinct roads and networks. Monitoring changes of road condition over time. Predicting the cost of travelling on the road.

26 THANK YOU Roughness A Smoother Ride
In addition to influencing driver satisfaction, pavement smoothness affects driver safety and mobility. Smoother roads increase fuel efficiency and decrease vehicle wear. THANK YOU


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