Roadroid - Reseach and Innovation for Swedish Transport Admin 2014

www.roadroid.comwww.twitter.com/roadroid

Lars Forslöf

Founder/CEO

100.000 km road condition data

surveyed by a motorist club

Transportforum 9 Januari 2015


This presentation

1. Introduction to technology

2. The projects 3 main issues:

1. How accurate is the data?

2. How can data be collected?

3. How can data be used

3. Summary/questions

2


How does it work: The app use the phone's accelerometer and analyzes vibrations from the vehicle in

100 Hz. Data is saved every second (1 Hz) with GPS-coordinates.

ww

w

Export

-Text files as

sections of

selectable lengths.

-Points o links to

shape files.

-Import in ex.

HDM4.


Roadroid surveys IRI according to IQL 3

• The world banks 4 Information Quality Levels (IQL) [1]

– Class 1 - Precision profilers (RST - laser – mycket exakt)

– Class 2 – Andra profilometrar (äldre/manuella metoder)

– Class 3 – IRI värde som korreleras mot vibrationsmätning

– Class 4 – Subjektiv klassning - okulärbesiktning


Roadroid - Estimated och Calculated IRI

• eIRI

– Make a selection of samples (not RMS) in a loop of 100 Hz, and estimates IRI.

Formula developed in correlation with IQL1 measurements (2012).

– Use a complex speed compensation (designed for paved road)

– Speed: 20-100 km/h

– Uses a setting of 3 car types: Small, Medium/Large-4WD/Jeep

– Research by University of Auckland found 81% corresponding to IRI [3], [4].

– sensitive to sudden shocks and rough texture.

• cIRI

– use QC (quarter-car systems) IRI algorithm [1]

– has an option to adjust sensitivity

– Requires constant speed of 60-90 km/h to keep accuracy

– calculates IRI for a given section length

– less sensitive to sudden shocks and rough texture.


Data serie with eIRI and cIRI

6


Quick analysis in web polygon


Show changes over time

• Easy to collect daily/weekly roughness data

• Compare % of different classes, for same links in different times.

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.


When does it happen?

How ”strong” is it?

What happend - where?

How was it afterwards?

Example frost heave


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Motormännens inspections: • Presets: 12 cars á 1500 mil - Result 92.000 km

• Two counties for correlation to IQL-data

• Interview with drivers/operators of qualitative result


Road Survey Technology in Sweden

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IRI-data from IQL1 resp. Roadroid

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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

VYM

Roadroid


Matching to road link

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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


Data from IQL1 and Roadroid for same link

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Each row is a link, ObjectID.(not a homogenus section)

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0,00

1,00

2,00

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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

2

0,00

1,00

2,00

3,00

4,00

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6,00

7,00

8,00

avgirivh

avgeiri

avgciri

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Summary of correlation: IQL1-Roadroid

1. In comparison to a large group of whole OID (0,2-5 km links) Roadroid

achieve a correlation factor (R2) of 0.6. Often even more accurate.

2. For 100-metre sections in 80 km/h, Roadroid reach eIRI 0.72/cIRI 0.77.

Within a limited type of road class it is possible to reach a higher.

3. Within a certain speed range, and with the right settings its possible to

survey down to 20-meter sections.

4. The correlation is better on poor paved roads, with higher and more

variable IRI.

5. Good roads with long IRI provides a smaller span and makes it more

difficult to correlate.

6. IQL1 seems more dynamic: With higher values on poor roads – and lower

values on good roads. This can provide a possible basis for a development

of the Roadroid analysis formula.

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Qualitative evaluationTwo questions to the drivers/operators

(1=not at all and 10=perfect)

1: If you look at the map of the area you surveyed, how much do you think the

result conforms to your own view? Answer: Average 8.4

2: How do you think the app performed during measurement? Did it register

bumps in the road surface, etc? Answer: Average 9.0

Text comments:

• Roadroid is a very good feature. We miss not having the whole year to measure, even in winter

and spring. It gave great results. And it was nice to view the police and say what reality looks

like. The police and the other was very impressed when I showed up the features and results.

• After having learned to protect the unit from the Sun with a "screen" and replaced a device it was

easy to use! However, the unit locked sometimes completely without reason! Forced shutdown

was only able to start all over again!

• The unit did not register long deep depressions in the road surface. Not either rutting.

• If it was too hot weather we could not use the charger, we had to take it into the house and charge

it overnight.

• To take photos – and touch the screen - the unit came out of position some times.

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How can data be gathered?

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Motorist club inspection

Road owner

Inspection

Contractors

News paper

distributor


How can data be collected?

Collection units How often

Maintenenace:

Benefit/Values

Traffic information:

Benefits/Value

Road owners –

contract manager

1 - 3 per

quarter

Frost heave, Bearing

capacity, load restrictions

Tactical follow ups

General / Comfort

Third party controls

consultants

1-3 per

month

Objective dialogue

Comparisons.

Contractors

Inspections

2-8 per

month

Operative control. Climate

effects Sign placing, Actions,

Gravel roads!

Post/Newspaper

distributor

5-6 per

week

Support to operative/tactial

actions. Winter! Guide IQL1. Winter roads, Bump Warnings

Motorist club

Yearly Inspections

~100.000

km yearly

Can complete IQL1. General / Comfort

Motorist club members

(Community)

Daily

/

Variety

Explore how crowd can work

Winter roads, Bump Warnings

Crowd Possibly cities, potholes,

winter roads

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Collection units How often

Maintenenace:

Benefit/Values

Traffic information:

Benefits/Value

Road owners –

contract manager

1 - 3 per

quarter

Frost heave, Bearing

capacity, load restrictions

Tactical follow ups

General / Comfort

Third party controls

consultants

1-3 per

month

Objective dialogue

Comparisons.

Contractors

Inspections

2-8 per

month

Operative control. Climate

effects Sign placing, Actions,

Gravel roads!

Post/Newspaper

distributor

5-6 per

week

Support to operative/tactial

actions. Winter! Guide IQL1. Winter roads, Bump Warnings

Motorist club

Yearly Inspections

~100.000

km yearly

Can complete IQL1. General / Comfort

Motorist club members

(Community)

Daily

/

Variety

Explore how crowd can work

Winter roads, Bump Warnings

Crowd Possibly cities, potholes,

winter roads

Hur kan data samlas in

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Two users:

1) Maintenance/pavement and

2) Traffic information

– General / Comfort and

– Winter roads, slippery roads, warn for bumps

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Comfort!


Comfort based route planning

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• Alternativ 1

– xx långt

– zz komfortabelt

• Alternativ 2

– pp långt

– kk komfortabelt


Maintenance – pavement planning

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In perspective of the “accuracy” discussion. Asset management is optimized with the

right decision, based on current data of good quality:

• In cold winter countries: IQL1 surveys are made in summer.

• Data processing and data imports into Pavement Management System in fall/winter.

• After the winter it is frost heave…It can change the pavement allot!

It takes a year from measurement to the pavement work.

Advanced models can predict the evolution, but winter can affect much…

• Moisture: how much water was in the way the body on the autumn

• Temperature: Cold/Frost depth, fluctuations around zero (thawing/Frost).

• Winter Road/Traffic: Ice removal, plowing, sanding, salting, studded tires.

• Extreme load: extreme amounts of timber after a storm

Many roads are only surveyed every second or third year ...

Bad road parts, or part with gravel/dirt cannot always be measured IQL1.


Possible benefits in pavement planning?

Update Pavement/Road Management System, with fresh

IRI values immediately after winter!

- Indicate adjustments in the assets management…

- Influence planning of coming summers IQL1 surveys.

If the situation has changed significantly, IQL1 can

check up more precisely.

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Frost heave, Floodings, Tsunamis..

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59%

42%48%

71% 68%

18%

22%19%

11% 13%

11%

14% 13%

7% 10%

12%22% 20%

11% 9%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Mars April Maj Juni Juli

Dålig

Ej OK

OK

Bra

4234 30 35

4157 57 58

45 41

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

W9 W10 W11 W12 W13 W14 W15 W16 W17 W18

Dålig

Ej OK

OK

Bra


Gravel roads…

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Of the Swedish state road

network of 100.000 km, 19,300

km are gravel roads (exclusive

all private forest roads).

• Frost thaw season (spring)

• Planing/Corrugating

• Regravelling

• Good support with

simple/quick GPS Photo.

Easy to use, robust, cheap ...


Winter roads

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Before ice grading:

-Road users complain, and

the contractor has to check

the need (subjective).

-Grading is an expensive

effort by subcontractor.

- After action: If grading or

plowing is not done well,

the result is bad.

= Useful in controlling the

operation and quality of

work.

Simple, robust, cheap ...

Friction measurement, like

"Coralba".


Performance based Maintanance

• Move the focus from the "exact" spec on what to do to what the

outcome is. Input->Output->Outcome.

• Stimulating innovation and the development of new and

sustainable solutions.

• New Key Performance Index/Indicators needed to evaluate the

outcome of certain technologies.

• Today the subjective assessments of a number of things along

the roads and highways (pen and paper).

• Smart phone data can provide a continuous data collection, and

with automated reports show changes over time.

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Pilot on E22, Kalmar-Östergötland

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Survey of roughness, effective visual registration of cracks, potholes etc

Automated report where actual situation and development trend is clearly visualized.


County maps

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Project summary1) How consistent Roadroid data?

– Correlates (R2) on to IQL1 between 0.6-0.8.

– Results fits very well with the motorists opinion

– There is a huge amount of data should be analyzed further.

2) How can data be collected, ex?

- The motorist clubs yearly collection

- Contractor/client – weekly updates

- Newspaper/mail distributor – Daily updates.

3) How can the data be used?

• Maintenance: Supplement to IQL1 – comprehensive and up-to-date.

• Maintenance: Performance based contract, new KPI:s

• Maintenance: Winter highways/roads and gravel/dirt roads.

• Traffic information: In winter and for comfort based route planning

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Awards

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November 2014

Februari 2013 – Global Champion, World Summit Award (FN) Övrigt:


Thanks for listening!

• Questions/discussion?

www.roadroid.com

[email protected]

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http://www.roadroid.com/

mailto:[email protected]


Referenser

• [1] Michael W. Sayers, Thomas D. Gillespie, and Cesar A. V. Queiroz, “The

International Road Roughness Experiment: Establishing Correlation and a

Calibration Standard for measurements,” World Bank Technical paper

number 45, Washington DC, 1986.

• [2] K.E.Tarr, “Evaluation of Response Type Application for Measuring

Road Roughness”, University of Pretoria, South Africa, 2013

• [3] Myles Johnston. “Using cell-phones to monitor road roughness”,

University of Auckland, Auckland, New Zealand, 2013

• [4] Tasnimul Islam. “Using cell-phones to monitor road roughness” ,

University of Auckland, Auckland, New Zealand, 2013

• [5] C. Bennet. 2013_wb_trends_road_asset_management, The world bank

• [6] M R Schlotjes, A Visser, C Bennet. Evaluation of a smart phone

roughness meter, University of Pretoria


Extra 1 - Roughness and Texture

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Bad RoughnessBad Texture

Good RoughnessBad Texture

Bad RoughnessGood Texture

Good RoughnessGood Texture

1)

2)

3)

4)


2014 we cooperate with universities in over 10 countries- something we want to atleast double during 2015!

Roadroid - Reseach and Innovation for Swedish Transport Admin 2014

Technology

Transcript of Roadroid - Reseach and Innovation for Swedish Transport Admin 2014