training 1.2 - 2015
TRANSCRIPT
Lars Forslof
CEO/FounderRoadroid
ROAD CONDITION MONITORING WITH SMART PHONES
Introduction/Training
2015
Lars Forslöf, Founder Roadroid
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
Sweden• 9 million inhabitants
– 80% of population in south
– Stockholm - Capital 1,5 million
• Industry– Minerals and forest industry
– Volvo, Scania, Sandvik, IKEA, ABB, SKF, Ericsson
– Design/Architecture/Music/Tourism
• High level of new innovations– as Bluetooth, Spotify, Skype
• Infrastructure challanges– Low populated areas in north
– Winters: -30° celsius and > 1 meter snow
– Frost heave/thaw in spring
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
The Road as a system
Why asset management?- to optimize the economy for my roads with maintenance!
Min
imu
m a
ccep
tab
leG
OO
D
New Road
Time / Years
Traffic wear
It is expensive with poor roads!Accidents, Car damages, Travel time, Fuel consumption…
But if i wait to long…it is very very expensive
Road maintenancecost money
Actions before its too late saves money
Example - Vehicle operation costshttp://www.pavementinteractive.org/article/life-cycle-cost-analysis
Where is Roadroid in the process?It is to collect and monitor data!
http://ntl.bts.gov/lib/12000/12100/12140/pdf/Kerali.pdf
Min
imu
m a
ccep
tab
leG
OO
D
Time / Years
IRI >2-4
It is very expensive with poor roads!Accidents, Car damages, Travel time, Fuel consumption…
IRI 4
IRI > 4
Unit assembling - hands on training
HDM4http://www.hdmglobal.com
A system and standard for optimizing your maintenance actions, Decision support, analysis and evaluation of actionsIRI is one possible input, but it also use other parameters as traffic flow, rutting, ravelling, shoveling, edge breaks, cracking etc.
International Roughness Indexhttp://en.wikipedia.org/wiki/International_Roughness_Index
• IRI is measured using profilometers, or by correlating the measurements to an IRI calculated from a profile.
• Using World Bank terminology, these are respectively called Information Quality Levels (IQL), representing the accuracy of the measurements.
– Class 1 - Precision profiles
– Class 2 - Other profilometric methods
– Class 3 - IRI by correlation ROADROID
– Class 4 - Subjective ratings
• IQL-1 systems typically report the roughness at 10–20 m intervals;
• IQL-3 at 100m+ intervals. The data can be presented using a moving average to provide a "roughness profile".
Class 4 – Subjective rating
How does it measure?
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Serie1
Serie2
Serie3
One point each second
Analyse 100 vibrations -> 1 value per second
(X,Y RC) 620029.012, 6782994.850, 3,5
Estimated IRI per road section
Dots matched to road links from open street map
Dots-layerEvery secons
Dots matched to road links(from open street map)
Dots-layer(every second)
Average eIRI
Bad RoughnessBad Texture
Good RoughnessBad Texture
Bad RoughnessGood Texture
Good RoughnessGood Texture
1)
2)
3)
4)
eIRI vs. cIRI (calculated IRI)
• eIRI– Using eIRI needs a linear conversion formula – Extensive IRI correlation studies to obtain the formula– Data collection speed paved roads - 20 – 100 km/h– Research by independent universities has found that eIRI have a 81%
correlation with IRI laser measurement systems [3][4] PAVED ROAD– eIRI is sensitive for sudden impacts and surface/micro roughness/gravel
• cIRI– use the QCS (quarter-car system) IRI algorithm [1]– have a vehicle sensitivity adjustment– need a fixed speed between 60 - 90 km/h to work correctly– cIRI calculates IRI for a given section length and is less sensitive for sudden
impacts and micro surface.– Different settings is needed on different roads and different speed
Tuning cIRI
!!! IMPORTANT !!!TO MAINTAIN ACCURACY
Make a setting table
Car type 1 Asphalt Gravel Earth/dirtSpeed 80 km/h 60 km/h 40 km/h cIRI-sensitivity 1,6 2,2 2,8cIRI length 40 m 100 m 200 m
ACKNOWLEDGEMENTS
International Road Federation
Global Road Achievment Award
The Kartographic Society - Innovation award (Sweden, March 2013)
European Satellite Navigation Competition -Regional winner (Munich, October 2012).
UN World Summit Award - Global Champion in eGovernance (Abu Dhabi, February 2013)
Android programming expert, Hans Jones, and
Web/GIS/database developer Tommy Niittula.
Lars Forslof (me)
+46-72-242662021
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
Expressway Section 1
cIRI (1,5) Right – different vehicles
cIRI Left
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cIRI Toyota Left
cIRI Honda Left
Expressway Section 1
cIRI (1,5) Right and Left same vehicle
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cIRI Toyota Right
cIRI Toyota Left
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cIRI Honda Right
cIRI Honda Left
Expressway Section 1
cIRI and cIRI (1,5) Right - same vehicle
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eIRI Honda Right
cIRI Honda Right
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eIRI Toyota Right
cIRI Toyota Right
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eIRI - Honda Right
cIRI - Honda Right
eIRI and cIRI – Myo Chaung road
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100
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eIRI - Toyota Right
cIRI - Toyota Right
cIRI set to 1,0 or 1,25
cIRI set to 1,5
Section length
!!! IMPORTANT !!!TO MAINTAIN ACCURACY
Make a setting table
RAV4 Asphalt Gravel Eart/dirtSpeed 80 km/h 60 km/h 40 km/h cIRI-sensitivity 1,6 2,0 2,5cIRI length 50 m 100 m 200 m
31
Using the built in camera with GPS
Plan for data collection
• Important to make a good plan
• Sketch on Paper maps – bring in car
• Connect to name - Section ID
• Divide in sub-sections
SR150100SR150110
SR150130
SR150120
Criterias for sections
Clear start - end points (land marks)
Length: Min 1 km - Max 10 km
Changes in road parameters such as
road width and surface type
Major intersection
Changes in topography
Administrative boundaries
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
Support for visual inventorys
Visual input of Rutting, Cracks, etcsaved with GPS-coordinate each second
Same logging every second, same mapinterface, same aggregation in sections
Inventory parameters
GPS HD Video
Input by smartphonesRoad inventory
Download directly:IRI, Speed, Grade in 20-200 m sections
Exports to your system:HDM4, RMMS, PMS, SIEM, SAMR, SPVG,
GIS/Shape, ex: SIGVial
App to Measure:IRISpeedPhotos
Spatial data/Shape:Longitud/LatitudeAltitude (Grade%)
App forVisual road inventorys:RuttingEdgebreakes, DrainageRailings etc
Research and trainingfor universities!
Anatalya, Turkey Balkh, Afghanistan
Vientiane, Laos
Lima, Peru
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in GIS tool Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
Spatial road data
If you have that, you can:
1) show the data on a map
2) use the ”area” to ask a databasea question
- What is the IRI for this road?
Spatial road data means a geographic (mathematic) definition of the road geometry.
Manual Vs Automated
Automatedreports
Data collection
Databasequestion
Maunalreports
Data collection
First time:Needs X00 hours of manual work to make sections in spatial format.Need x0 hours of development
Second time:Takes some hours to complete a full report of all 600 road links.
Every time:X00 hours of manual work.
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
The Roadroid Index
55
Road Condition Change report Q4 - 2012Gävleborg
Hudiksvall Contractor 69,4% 15,5% 7,4% 7,8% 65,8% 14,6% 8,5% 11,0%
1089 Km Phone 010-476 14 07 Q4 - 2012 Helår - 2012
Road no. Traffic Class Length Comments Good Sat Usat Poor TREND Good Sat Usat Poor eIRI avg
E4 14000 1 143 93,9% 4,6% 0,9% 0,5% -3,4% 97,4% 2,0% 0,4% 0,3% 1,8
83 8300 2 167 Salt road 88,9% 7,4% 2,2% 1,5% 3,3% 85,6% 8,0% 3,2% 3,2% 2,6
84 7500 2 210 Salt road 90,9% 6,1% 1,7% 1,3% -1,6% 92,5% 4,8% 1,6% 1,1% 2,9
305 1200 3 105 76,7% 14,4% 5,3% 3,6% -0,6% 77,3% 13,3% 5,2% 4,1% 4,5
307 900 3 75 93,7% 5,2% 0,7% 0,4% 0,4% 93,3% 5,5% 0,8% 0,4% 3,7
539 300 3 33 Gravel road 9,1% 23,2% 24,2% 43,4% 7,5
583 1700 3 89 96,9% 2,6% 0,2% 0,3% 0,0% 96,9% 2,0% 0,6% 0,5% 2,3
660 1850 3 64 88,6% 8,3% 0,6% 2,5% 9,1% 79,5% 9,7% 4,5% 6,3% 6,7
Good for Q4 minus Good for all year.
Network monitoring, Myanmar
Road Condition Map
MyanmarShan stateFeb-Oct 2014
<4 good (26%)4-6 fair (18%)6-8 poor (16%)>8 bad (39%)
Legend:(eIRI)
Points per State – 1,4 millon points
eIRI per state/region eIRI <4 eIRI 4-6 eIRI 6-8 eIRI >8 Total eIRI <4eIRI 4-6 eIRI 6-8 eIRI >8Speed eIRI
Ayeyarwady 61135 29696 22607 52374 165812 Ayeyarwady 37% 18% 14% 32% 43 6,9
Bago 139219 38932 25763 36068 239982 Bago 58% 16% 11% 15% 50 4,5
Chin 54 120 141 725 1040 Chin 5% 12% 14% 70% 29 10,3
Magway 56154 39647 38918 90518 225237 Magway 25% 18% 17% 40% 39 8,8
Mandalay 75068 33618 26598 45534 180818 Mandalay 42% 19% 15% 25% 44 7,4
Mon 15176 4565 2792 2992 25525 Mon 59% 18% 11% 12% 48 5,8
Rakhine 86 152 198 650 1086 Rakhine 8% 14% 18% 60% 46 4,2
Kayah 4710 6413 7110 18144 36377 Kayah 13% 18% 20% 50% 31 9,3
Sagaing 1959 1926 1141 841 5867 Sagaing 33% 33% 19% 14% 48 5,4
Shan 89652 63455 55359 135694 344160 Shan 26% 18% 16% 39% 7,3
Tanintharyi 32448 20952 15911 33928 103239 Tanintharyi 31% 20% 15% 33% 38 6,8
Yangon 36207 21169 16819 23476 97671 Yangon 37% 22% 17% 24% 48 5,8
SUMMARY 5E+05 260645 213357 440944 1426814 36% 18% 15% 31%
0 50000 100000 150000 200000 250000 300000 350000 400000
Ayeyarwady
Bago
Chin
Magway
Mandalay
Mon
Rakhine
Kayah
Sagaing
Shan
Tanintharyi
Yangon
Total amount of RC-points - Myanmar per region
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Ayeyarwady Bago Chin Magway Mandalay Mon Rakhine Kayah Sagaing Shan Tanintharyi Yangon
All roads % per RC class - Myanmar per state/regions
eIRI <4 eIRI 4-6 eIRI 6-8 eIRI >8
0 10 20 30 40 50 60
Ayeyarwady
Bago
Chin
Magway
Mandalay
Mon
Rakhine
Kayah
Sagaing
Shan
Tanintharyi
Yangon
Average speed in km/h - Myanmar per state
Existing
Make proper structure!- prepare for a spatial database
Code No1 No2 Region Sec NameofRoad RoadPartName Road Code State Code StartLocationName StartM StartF StartKm EndLocationName StopM StopF StopKm LengthKmRoadWidthSlengthM SlengthF Length KM Remark1
IC 1 1 Kachin State Myit Kyi Nah – Pan Souk – Ledo Road 0 0 0 177 0 283,2 283,2 300 177 0 283,2
IC 2 1 Kachin State Washong-Sadone-Kan pike ti Road (New) 13 0 20,8 63 0 100,8 80 300 50 0 80
IC 3 1 Kachin State Moe Mauk-Gravel Camp-Sein Lon-Lwal Jal 0 0 0 47 4 76 76 300 47 4 75,2
IC 4 1 Kachin State Phar Saung-Mal See Nan-Mal Se`-Nan Mang Road 0 0 0 40 0 64 64 300 40 0 64
IC 5 1 Kaya State Nan Mang-BP(13) Road 0 0 0 10 0 16 16 300 10 0 16
IC 6 1 Kayin State Ba Ahn-Htone Eine Road 0 0 0 3 2 5,2 5,2 300 3 2 4,8
IC 7 1 Kayin State Zar Tha Pyin-Kyone Phe`-Kyar kalay Road 0 0 0 15 3 24,6 24,6 300 15 3 24
IC 8 1 Kayin State Mawlamyaine-Zartha pyin-Eindu Road 0 0 0 9 5 15,4 15,4 300 9 5 14,4
IC 8 10 Mon State Mawlamyaine-Zartha pyin-Eindu Road 9 5 15,4 64 5 103,4 88 300 55 0 88
IC 9 1 Mon State Than phyu za yat-Bayar Thone Suu Road AH01 0 0 0 9 5 15,4 15,4 300 9 5 14,4
IC 9 10 Kayin State Than phyu za yat-Bayar Thone Suu Road AH01 9 5 15,4 64 5 103,4 88 300 55 0 88
IC 10 1 Mon State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Tha Htone –Ba Ahn Road AH01 0 0 0 8 1 13 13 300 8 1 12,8
IC 10 2 Kayin State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Tha Htone –Ba Ahn Road AH01 8 1 13 22 5 36,2 23,2 300 14 4 22,4
IC 10 3 Kayin State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Thanlwin Bridge Approaching RoadAH01 0 0 0 9 0 14,4 14,4 300 9 0 14,4
Code No1 No2 Region Sec NameofRoad RoadPartName Road Code
IC 1 1 Kachin State Myit Kyi Nah – Pan Souk – Ledo Road
IC 2 1 Kachin State Washong-Sadone-Kan pike ti Road (New)
IC 3 1 Kachin State Moe Mauk-Gravel Camp-Sein Lon-Lwal Jal
IC 4 1 Kachin State Phar Saung-Mal See Nan-Mal Se`-Nan Mang Road
IC 5 1 Kaya State Nan Mang-BP(13) Road
IC 6 1 Kayin State Ba Ahn-Htone Eine Road
IC 7 1 Kayin State Zar Tha Pyin-Kyone Phe`-Kyar kalay Road
IC 8 1 Kayin State Mawlamyaine-Zartha pyin-Eindu Road
IC 8 10 Mon State Mawlamyaine-Zartha pyin-Eindu Road
IC 9 1 Mon State Than phyu za yat-Bayar Thone Suu Road AH01
IC 9 10 Kayin State Than phyu za yat-Bayar Thone Suu Road AH01
IC 10 1 Mon State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Tha Htone –Ba Ahn Road AH01
IC 10 2 Kayin State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Tha Htone –Ba Ahn Road AH01
IC 10 3 Kayin State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Thanlwin Bridge Approaching RoadAH01
IC 10 4 Kayin State Tha Htone-Ba Ahn-Kokkareit-Myawaddy Road Ba Ahn-Pai Yahn Road AH01
StartLocationName StartM StartF StartKm EndLocationName StopM StopF StopKm LengthKmRoadWidthSlengthM SlengthF Length KM
0 0 0 177 0 283,2 283,2 300 177 0 283,2
13 0 20,8 63 0 100,8 80 300 50 0 80
0 0 0 47 4 76 76 300 47 4 75,2
0 0 0 40 0 64 64 300 40 0 64
0 0 0 10 0 16 16 300 10 0 16
0 0 0 3 2 5,2 5,2 300 3 2 4,8
0 0 0 15 3 24,6 24,6 300 15 3 24
0 0 0 9 5 15,4 15,4 300 9 5 14,4
9 5 15,4 64 5 103,4 88 300 55 0 88
0 0 0 9 5 15,4 15,4 300 9 5 14,4
9 5 15,4 64 5 103,4 88 300 55 0 88
0 0 0 8 1 13 13 300 8 1 12,8
8 1 13 22 5 36,2 23,2 300 14 4 22,4
0 0 0 9 0 14,4 14,4 300 9 0 14,4
6 5 10,6 9 0 14,4 3,8 300 3 -5 4,8
• % of 4 IRI classes for a specific road section in spring
What happens atEarth quakes?Tsunanis?
How bad…Where…
Monitor Roughness changes over time
Training schedule
Roadroid introPrinciple functionsSetting table - different cars/road types.Development since jan 2014
Geographic Information SystemsIntroduction Spatial dataDownload shape files from webOpen in Qgis
Web featuresImport history and file detailsFile downloads and section lengthCharts in Excel
Spatial road databaseSaving datafilesData base structure/namingUsing regions for questions
Road Inventory AppUse in PracticeUse of web featuresGPS-video
Spatial data for reportsExamples of roads, streets in citiesRoad condition change reports
From Roadroiddots to spatial
links data
From Roadroiddots to spatial
links data
Basic road geometry
Basic road geometry
IRI
0-20 m 20-40 m 40-60 m 60-80 m Osv… Vägens längds-riktning
IRI
Data varje sekund med ko-ordinat – matchning till länk Vägens längds-riktning
IRI
0-20 m 20-40 m 40-60 m 60-80 m Osv… Vägens längds-riktning
IRI
Data varje sekund med ko-ordinat – matchning till länk Vägens längds-riktning
Ett unikt objekt-ID (OID)length; irihv; avgspeed; nopoints; eiri; ciri
Medel för IRI höger o vänster (irihv)
Medel för hastighet, antal punkter för länken, eIRI ocIRI
IRI från Vägytemätning IRI från Roadroid
0,00
1,00
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01
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81
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14
81
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1
avgirivh avgeiri avgciri
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
1 71
31
92
53
13
74
34
95
56
16
77
37
98
59
19
71
03
10
91
15
12
11
27
13
31
39
14
51
51
15
71
63
16
91
75
18
11
87
19
31
99
20
52
11
21
72
23
22
92
35
24
12
47
25
32
59
26
52
71
27
72
83
28
92
95
30
13
07
31
33
19
32
53
31
33
73
43
34
93
55
36
13
67
37
33
79
38
53
91
39
74
03
40
94
15
42
14
27
43
34
39
44
54
51
45
74
63
46
94
75
48
14
87
49
34
99
50
55
11
avgirivh
avgeiri
avgciri
1
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
avgirivh
avgeiri
avgciri
1
2
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 101 103 105 107
avgirivh
avgeiri
avgciri
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00
1 71
31
92
53
13
74
34
95
56
16
77
37
98
59
19
71
03
10
91
15
12
11
27
13
31
39
14
51
51
15
71
63
16
91
75
18
11
87
19
31
99
20
52
11
21
72
23
22
92
35
24
12
47
25
32
59
26
52
71
27
72
83
28
92
95
30
13
07
31
33
19
32
53
31
33
73
43
34
93
55
36
13
67
37
33
79
38
53
91
39
74
03
40
94
15
42
14
27
43
34
39
44
54
51
45
74
63
46
94
75
48
14
87
49
34
99
50
55
11
avgirivh
avgeiri
avgciri
1
2
2
How does it measure?
-4
-2
0
2
4
6
8
10
12
14
16
1
33
65
97
12
9
16
1
19
3
22
52
57
28
93
21
35
3
38
5
41
7
44
94
81
51
35
45
57
7
60
9
64
16
73
70
5
73
77
69
80
1
83
3
86
58
97
92
9
96
19
93
10
25
10
57
10
89
11
21
11
53
11
85
12
17
12
49
12
81
13
13
13
45
13
77
14
09
14
41
14
73
15
05
15
37
15
69
16
01
16
33
16
65
16
97
17
29
17
61
17
93
18
25
18
57
18
89
19
21
19
53
19
85
20
17
20
49
20
81
21
13
21
45
21
77
22
09
22
41
22
73
23
05
23
37
23
69
24
01
24
33
24
65
24
97
25
29
25
61
25
93
26
25
26
57
26
89
27
21
27
53
Serie1
Serie2
Serie3
Analyse 100 vibrations -> 1 value per second
(X,Y, IRI) 620029.012, 6782994.850, 3,5
Estimated IRI per 20-100 m OR road section in db
Basic road geometry
Road WeaterInformation System
Solar power trafficcounters
Bluetooth traffic counter
Traffic Management
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