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Transcript of Portorož, Slovenia Alex WrightAlex Wright TRL Infrastructure DivisionTRL Infrastructure Division...
Portorož, Slovenia
•Alex WrightAlex Wright
•TRL Infrastructure DivisionTRL Infrastructure Division
•Group manager, Technology DevelopmentGroup manager, Technology Development
•[email protected]@trl.co.uk
Developing the automatic measurement of surface condition on local roads
Portorož, Slovenia
Measuring condition at traffic-speed in the UK
o UK condition surveys measure• Longitudinal profile• Transverse profile• Texture profile• Cracking (automatic)• Geometry
o Annual coverage • TRACS: 40,000km motorway and trunk
roads • SCANNER: 80,000km local road network
o Surveys carried out to an end result specification
Portorož, Slovenia
“UK” Systems
• Accredited Systems:• Jacobs
– Ramboll RST26, RST27• WDM
– RAV1, RAV2, RAV3, RAV4• DCL
– Roadware ARAN1, ARAN2
Portorož, Slovenia
UK trunk roads - TRACS
Portorož, Slovenia
UK local roads (rural) - SCANNER
Portorož, Slovenia
UK local roads (urban) - SCANNER
Portorož, Slovenia
Use of the Data
o Local use• Parameters reported over 10m lengths for local use
o Network use• For trunk roads total length of poor values reported
• Single HA performance indicator (PI)
0
10
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90
A
Road category
Pro
port
ion
(%)
Red
Amber
Green
• For local roads a Road Condition Index (RCI) is produced every 10m
• Reports “overall” condition score• Distribution of RCIs over the local
authority defines network condition (LA Indicator)
• Potential use in allocation of funding across authorities
Portorož, Slovenia
o Local roads differ from trunk roadso New methods required to maximise value of local road datao Research to improve the use of the survey data
• Measuring ride quality on local roads using shape data• Using texture to assess surface deterioration on local roads• Measuring edge deterioration on local roads
o Work concentrated on the use of shape datao Began with consultation to find out what users needed in
practice
Enhancing the use of data from local roads
Portorož, Slovenia
“Shape” data collected at traffic-speed
6566676869707172737475
Chainage (m)
Portorož, Slovenia
o Consultation with engineers found that• Little importance placed on longitudinal profile data• Key structural measure is cracking and rutting• Engineers desire a reliable assessment of general ride
quality (functionality)• But engineers key concern is defects giving rise to
bumps (user complaints)o Concluded that methods needed to
• Reliably identify lengths with poor ride quality• Identify general locations giving rise to bumps
Measuring ride quality on local roads - consultation
Portorož, Slovenia
Measuring ride quality - data collection
o A practical investigation to relate surface profile to user opinions on local roads
o Several routes surveyed, including sections known to be pooro Profile data provided by HARRIS1 profilometer
• Measurements in both wheel tracks (and across survey width)o User surveys:
• Car surveys• Motorbike survey• Utilising on-board data collection
with GPS referencing• Reported on ride and bumps• Repeat surveys for consistency
Portorož, Slovenia
Considering general ride quality
3m 5m0.000000001
0.000001
0.001
1
1000
1.00E-01 1.00E+00 1.00E+01 1.00E+02
Wavelength
Po
wer
100m lengths where dial >2100m lengths where dial <=2
0.37
5916
0.49
5487
0.65
3091
0.86
0827
1.13
4638
1.49
5543
1.97
1245
2.59
8258
3.42
471
4.51
4041
5.94
9865
7.84
2396
10.3
3690
2
42400
42410
42420
4243042440
42450
42460
42470
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4249042500
42510
42520
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4255042560
42570
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42600
4261042620
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42650
Wavelength (m)
Sit
e C
hai
nag
e (m
)
1.38-1.4
1.35-1.38
1.33-1.35
1.3-1.33
1.28-1.3
1.25-1.28
1.23-1.25
1.2-1.23
1.18-1.2
1.15-1.18
1.13-1.15
1.1-1.13
1.08-1.1
1.05-1.08
1.03-1.05
1-1.03
0.98-1
0.95-0.98
0.93-0.95
0.9-0.93
o Wavelet Decomposition
o PSD
1m – 5m
o IRI, Ride Number, Profile Indexo MA and enhanced varianceo Coefficient de planeiteo Waveband Energyo Standard Deviation
Portorož, Slovenia
General ride quality - wavelength response
o IRI
o 3m Variance
Portorož, Slovenia
Parameter for general ride quality
o Predicting general ride quality on local roads• 1-5m wavelength features cause the users most
discomfort. • 3m enhanced variance agreed best with user opinion of
underlying ride quality. Other measurements agreed no better with the user’s opinion.
• 10m enhanced variance showed some agreement (effects of longer wavelengths on truck drivers).
• Wavelengths over 20m - little or no agreement with usero Effect of measurement (line)
• Offside measurements contributed to 33% of agreement with user opinion.
• Multiple measurement lines around the wheelpath did not improve agreement
Portorož, Slovenia
Measuring “Bumps” on local roads
o User surveys recorded bumps using button presseso Wavelet analysis suggested wavelengths of interest lie
between 1 and 3m.o Existing measurements (variance, IRI etc) did not reliably
report the locations of the features causing this bump-like discomfort.
0.5m
2.5m2
2.2
2.4
2.6
2.8
3
3.2
3.4
3.6
3.8
4
0 5 10 15 20 25 30 35 40 45Wavelength (m)
No
rmalised
Po
wer
Button press
No button press
Portorož, Slovenia
Measuring “Bumps” on local roads
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10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000
Chainage (m)
Dial
val
ue
Cat4 3m enh var NSWT
Cat 4 3m enh var OSWT
Dial value
Bump
Portorož, Slovenia
A parameter for “Bumps” on local roads
o Considered many approaches, e.g.• 1.25m enhanced variance, change of vehicle acceleration,
derivative of longitudinal profile (features too small to impact on a car’s tyre)
o The Central Difference Method • Calculates a “derivative” for each point along the road (profile
measurements {yi}, taken at distances {xi} along the road):
• Similarly for F’’.• The maximum of these values is calculated over 1m lengths.• If max(F’) and max(F’’) both exceed set thresholds, then the
length contains a bump and a value of “1” is reported for that length. Otherwise “0” is reported.
11
11)('
ii
ii
xx
yyixF
Portorož, Slovenia
Measuring “Bumps” with the CDM – local roads
o Tests to review locations where the bump measure responded• Reported 84% of user button presses.• Potential high number of false positives.• Inspection of 3D profile and video showed features of note
where CDM responds, but users had not always pressed the button.
o Concluded • This is an appropriate method for identifying “bumps”.• We should use a combination of this and 3m enhanced
variance for assessing general ride and bump density on local roads
Portorož, Slovenia
Testing on trunk roadsEasting and Northing
152500
162500
172500
182500
465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000
Easting
No
rth
ing
Portorož, Slovenia
Measuring “Bumps” – trunk roads
o Applied to whole of trunk road and motorway network.• 0.17% of network reported to contain bumps
o Subset inspected in closer detail:• Inspected 3D profile for 10% of locations• Visual inspection on site of 1% of locations
o Where 3D profile inspected:• 87% contained obvious bumps• Further 10% showed general unevenness
o Where site inspected,• 64% showed visible bumps on site• 24% were not “bumps”, but were poor bridge joints• 3% were bumps at surface change
Portorož, Slovenia
Measuring Edge deterioration - consultation
o Consultation with engineers found that • Edge deterioration universally considered an area for
concern• Key requirement for a measure to aid in defining
maintenance treatmento Features of interest
• Potholes in surface near edge• Overriding• Cracking of surface near edge• Edge supported or kerbed• Presence of patching
Portorož, Slovenia
Developing parameters for Edge Deterioration
o A fully automated measureo Utilising transverse profile
data • Firstly Identify the edge
strip o Edge Roughness
• Roughness within the edge strip
o Edge Stepping• Stepping at the
nearside of the edge strip
o Transverse Variance• Assessing roughness
across the pavement
Portorož, Slovenia
Edge deterioration parameters
Portorož, Slovenia
The Edge deterioration parameters
o Transverse edge roughness edge step unevenness
Portorož, Slovenia
Testing the Edge deterioration parameters
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0 20 40 60 80 100
Chainage, km
Nu
mb
er
of 1
0m
len
gth
s in
ea
ch
1k
m e
xc
ee
din
g
95th
pe
rcen
tile
lev
el
0
0.1
0.2
0.3
0.4
0.5
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0.7
0.8
0.9
1
CV
I E
dg
e D
ete
rio
rati
on
, a
ve
rag
e s
ev
eri
ty o
ve
r 1
km
Edge Step L2 Edge Step L1 CVI-B_ED
Portorož, Slovenia
An Indicator for Edge Condition
o Four parameters provide a complicated picture of condition• Better to report the general edge condition
o The ‘Edge Deterioration’ indicator• Combines all four SCANNER Initial Edge Deterioration
Parameters• Is a weighted combination of parameters after applying
thresholds and normalisation• Provides a single number to the engineer• Is based on the logic of the SCANNER RCI
Edge Det = Wryedge roughness + Wtvytrans variance + WE1yedge step 1 + WE2yedge step 2
Portorož, Slovenia
Testing the indicator for Edge Condition
o Comparison with site assessments
0
1
2
0 20 40 60 80 100Chainage (km)
Edge
Det
erio
ratio
n In
dica
tor
0
1
CVI e
dge
dete
riora
tion
(y/n
?)
Edge deterioration seen on video Edge Deterioration Indicator CVI Edge
Portorož, Slovenia
Testing the indicator for Edge Condition
o Proportion of roads having significant edge deterioration by manual surveys and the Edge Deterioration Indicator
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1.5
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A B C Unclassified
Ed
ge
Det
erio
rati
on
% >
50
0
2
4
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10
12
14
16
CV
I % w
ith
no
n-z
ero
sev
erit
y
Edge Condition indicator
CVI
Portorož, Slovenia
Conclusions
o Traffic-speed surveys have become widely applied in the UK on local roads under SCANNER (>100,000km/year)
o Local roads have particular defects o A research programme has developed a set of parameters for
reporting local road condition using data collected at traffic-speedo For ride quality
• Enhanced variance• A bump measure
o For edge deterioration• A set of edge deterioration parameters• An edge condition indicator
o These new parameters were introduced into SCANNER in 2007 for network level reporting