Life-Cycle of Engineering Systems: Emphasis on Sustainable
Civil Infrastructure – Bakker, Frangopol & van Breugel (Eds)© 2017 Taylor & Francis Group, London, ISBN 978-1-138-02847-0

The Relationship between Damages in Road Pavement and Customer
Feedback
Kiwako Takahashi

Dept. of Civil and Environmental Engineering, Kanazawa Institute of Technology

Sadao KimuraDept. of Civil and Environmental Engineering, Kanazawa Institute of Technology

Mamoru Moriyama

Central Nippon Expressway Co., Lid.

ABSTRACT: Throughout Japan the road surface condition of expressways is monitored on regular basis. IRI
is used as a measure of road roughness and visual inspection by expressway patrol teams is used to check for
emergency road damages. Inspection using IRI is carried out every two years. When emergency road damages, such as potholes, are detected by expressway patrol teams, emergency repairs are executed as soon as possible.In addition to IRI and visual surface inspection, some customers lodge complaints about the trafficabilityof the expressways. In this study, damage probability of road pavement was evaluated using inspection result
data between each interchange along an expressway. The relationship between damage probability and customer feedback for trafficability was also considered.

1 INTRODUCTION
In Japan, Road Act was revised in May 2014 due tothe accident of Sasago Tunnel in 2012. And in accordance with the incidents, the consciousness ofpeople for road facility has changed. Especially highsafety is required in expressway. In addition, expressway management companies are carrying out
daily and periodic inspections for structures of expressway and other related facilities. Besides they
have requirement of accountability for stakeholders.
Objects of these inspections are mainly classified into bridges, tunnels, pavement and facilities. In thisstudy we focus on road pavement.
In road pavement, there are the structural destructions and the functional destruction, which lose safety and comfort of user. Deteriorations and damages
Figure 1. Property Factors of Managing Pavement Including
occur depending on the usage of the road which is
Customer’s Complaint
traffic conditions, ground conditions, climate conditions and so on. For this reason, road have somerisks that damages which can’t be detected between
2 PROPERTY FACTORS OF MANAGING
inspection intervals may occur. On the other hand,
PAVEMENT INCLUDING CUSTOMER’S
some users of expressway lodge complaints when
COMPLAINTS AND POTENTIAL RISK
they encounter damages on the road. Such damage
included pothole and crack, and other unsafe roadWe defined the relationships between property facsurfaces. In considering accountability of pavement
tors,“consequence of road” “road surface property”
condition, to comprehend the road surface condition“customer’s
feedback’, as we think about the manis quantitatively with inspection records. However
agement including customer’s complaint. (See Fig.1)
relations between this condition and complaints
That is it is necessary for road manager to secure thelodged by users haven’t been described before.
quality of pavement considering consequence of
The purpose of this study is confirming the relaroad and customer’s feedback. Therefor, at first, wetionship between complaints lodged by users andneedto grasp the each relationship between thesedamages occurring on road surface.
1580

Figure 2. Inspection outline of property factors (2011, 2012, 2013 )three property factors.
Fig. 2 illustrates outline of inspection to grasp
property factors of objective road. The objective
road consider in this study is the Hokurikuexpressway which has been in service for over 30year. This object road has 27 interchanges and its total length is 258.9 km. We analyzed with investigation data form 2011 to 2013.
We conceive consequence of road to be the 24hour average number of passing vehicles per eachinterchange because this factor indicates circumstance of road with fact that how many vehicles use
the road.
We grasp road surface property with two inbestigations. First data set is record of road surface damages detected by daily visual inspection which iscarried out 4 times or 5 times every 2 weeks. Another data set is investigation record of pavement condition carried out every two year by a road surface
condition survey vehicle. Customer feedback iscomplaints that users lodge about trafficability ofexpressway.
With these 3 property factors, we reveal each relationship. Fig.3 shows an example of the relationship between traffic volume and occurrence probability of pavement damages. Occurrence probabilityof pavement damages is based the on daily visual inspection. Fig.4 shows an example of relationship between traffic volume and section average of IRI. IRI
is based on the investigation record of pavement
condition.

Figure 3. The relation between traffic volume and occurrence
probability of pavement damages

Figure 4. The relation between traffic volume and IRI average
per a section1581

Now, the rage both axes are high means thatmany users use the section of road, and also it meansthat the risk on safety and comfort is high. Thereforin this road section which risk is high, expressway
management companies need to endeavor to improve the pavement condition.
Correlations are not observed in these two figures.
3 CHARACTERISTIC OF ROAD SURFACEPROPERTY
We explain about the previously mentioned two data
sets as road surface property, and conduct comparison and consideration.

Figure 5. Number of damages in each category (total of2011, 2012 and 2013)
0.8

3.1 Damages of pavement
Figure 5 shows the total number of pavement damages in each category detected by daily visual inspection in 2011, 2012 and 2013. This inspection
carried out 4 times or 5times every 2 weeks depends
on traffic volume.
According to this inspection, pavement damages
are compounded from 74% pothole, 14% cracks, 5%rutting, 2% bumping and others 4％. In this study
the all kind of these damages are considered aspavement damages. Pavement damages found by
this inspection have each management threshold.
Potholes are dealt immediately with emergency
measure like patching after they are detected by thisvisual inspection. On other kind of damages, if they
are worse deterioration than thresholds, they are also
dealt as well as pothole or planned for maintenance.
Occurrence probability of pavement damages isnumber of pavement damages per unit length andper one inspection based on this daily visual inspection.

10.525 2𝜋

1 𝑥−1.651 2𝑒 −2( 0.525 )0.6
μ=1.651
σ=0.5252

0.5
0.4
0.3
0.2
0.1

0012345Figure 6. Normal distribution of IRI measurement for threeyears

Tale 1. Management thresholds of three items of investigationof pavement condition

Measuring Items
Target ofManagement
Target ofRepairing

3.2 Investigation of pavement condition

IRImm/mCracks%Rutting
Mm

2.7

1015

3.52025

0.20
Earthwork

Probability of pavement damages（/100m/1 inspection）

Another data set is investigation of pavement condition carried out every two year by a road surface
condition survey vehicle and evaluated by threemeasuring items, IRI, which is index of pavement
roughness, cracks and rutting every 100m. IRI, International Roughness Index, was proposed by theWorld Bank as index of evenness influencing ride
comfort. Crack is ratio of crack per unit area. Rutting is depth of unevenness in transverse direction.
These 3 items also have each two management
thresholds - target value of repairing and target value of management (Tab.1). If IRI = 3.5mm/m thenrepairs required soon and if IRI = 2.7mm/m then thesurface is carefully monitored.
For example, figure 6 shows the normal distribution of IRI measurement in three years. Two probabilities of excess thresholds are following below.

𝑓 𝑥 =

0.7

Bridges

0.15

Tunnels

0.10
0.05
0.00
0.0

1.0

2.0
3.0
IRI（mm/m/100m）

4.0

5.0Figure 7. The relationship between occurrence probability ofpavement damage and IRI measurements（𝑆1 ～𝑆26 ）1582

P(2.7 < x) = 0.022750
P(3.5 < x) = 0.000216

0.20Earthwork
Probability of pavement damages（/100m/1 inspection）

It can be explained by these results that management with
IRI is good standing.

3.3 The relation between damages of pavement andinvestigation of pavement condition
Fig.7, fig8, and fig9 illustrate each relationship between occurrence probability of pavement damage
and measurements of pavement condition (IRI,crack, rutting). Three kinds of pavement, “embankment”, “bridges” and “tunnels” are divided in thefigures because these construction is deference. It
can be confirmed that by these figures that occurrence probability of pavement damages is even highbelow the management thresholds for IRI, cracks,
and rutting. Therefor pavement damages occurring
sporadically such as potholes don’t entirely correspond with pavement condition.

Tunnels

0.10

0.05

0.00
010
Crack（％/100m）

2030Figure 8. The relationship between occurrence probability ofpavement damage and crack measurements（𝑆1 ～𝑆26 ）Probability of pavement damages（/100m/1 inspection）

0.20

4 THE RELATION BETWEEN COMPLAINTS
AND ROAD SURFACE PROPERTY
4.1 Reliability evaluation method on usercomplaints
Tab 2. Number of complaints and number of sections indicatedby userNumber of Complaints
Number ofWhich Can Be
Complaints
Identified
Damage Site
FY20115234
FY20125132
FY20134322

Bridges

0.15

Number ofAverage
Sections
Number ofPointed by Section Pointed
Complaints by A Complaint
77
2.27
51
1.59
60
2.73

Earthwork
0.15

BridgesTunnels

0.10
0.05
0.00
051015Rutting（mm/100m）
Figure 9. The relationship between occurrence probability ofpavement damage and rutting measurements（𝑆1 ～𝑆26 ）Tab 3. Reliability evaluation of user complaint
Hierarchy ofReliability

Reliability Ⅰ

Reliability Ⅱ

Reliability Ⅲ

Index of Reliability Evaluation

Keywords of complaint(2012)(1) States of Damage○(2) Location of Finding damage○(3) Fact Identified or not by inspection○(1) States of Damage△(2) Location of Finding damage△(3) Fact Identified or not by inspection△(1) States of Damage

×(2) Location of Finding damage

×(3) Fact Identified or not by inspection

×Numberof Cases
FY2011FY2012FY2013

Pothole, Cave-in, Rutting, Hole,
Bumping, Repair mark of hole,Dent, Impact, Swing, Shaking of tire,
Pulling out of ETC-card,
Uncontrolling steering wheel

15629

Pothole, Cave-in, Rutting,Hole, Bumping, Channel,
Deteriorarion with over time,
Impact, Gap, Damage, Patchwork,
Some onomatopoetic words likeshaky and bumpy.

172368Hole, Badly, Roughly,
Some onomatopoetic words likeshaky, bumpy, roughly and shabby

191449TOTAL51

1583

43146

the other hand Fig.15 is related to negative correlation for some reason. No relationship is observed inwith S16 and S23 – 26. According to that, most users tend to lodge complaints about sporadic damages
such as pothole and not about long span problems.

Number of complaints（/km）

2.0

ⅢⅡⅠ

1.5

1.0

0.5

0.0
S1 S3 S5 S7 S9 S11 S13 S15 S17 S19 S21 S23 S25

Section Number
Figure 10. Number of complaints user indicate in each section(total of 2011, 2012 and 2013)
0.12
Probability of pavement damages（/km/1 inspedtion）

More accurate time and point that complaints lodged
are sought to consist user complaint with pavement
condition. However one complaint often indicate
through some sections or it is impossible to identify
where. Complaints to the managing company aresomething only a few user lodge and they are quite
subjective. At first, reliability of user’s voice needs
to be analyzed.
Tab.2 shows a number of all complaints about radpavement ledged by users, a number of complaints
mentioning sections which damages exist, a numberof sections where complaints indicate, and average
number of sections pointed by one complaint, foreach year. Tab.3 illustrates the index of evaluation
to evaluate hierarchy of reliability, evaluation levelby each hierarchy of reliability, and keywords thatuser use. The indexes are (1) States of Damage, (2)Location of Finding Damage, (3) Fact Identified or
Not by Inspection. We check whether complain
mentions correctly or not in regard to (1) and (2),and whether to detect or not while inspection withattending complaint in regarding to (3). User complaint giving accurate information with these indexes categorized into reliability- Ⅰ and one givingnothing or vague information categorized into reliaility-Ⅱ. Reliability-Ⅲ is complaint ranking between the two indexes above.
Fig. 10 illustrates the result of reliability evaluation in each section in 2011, 2012 and 2013. It suggests there are specifically more reliability- Ⅰ
complaints in S16. And they are concentrated
around from S23 to 25. Reliability-Ⅰ complaint iscustomer feedback based on the fact. So it is required to be conscious in order to save the safety.
4.2 The relation between sections indicated bycomplaint and pavement damage

FY20110.10

S16

0.08S23～S26

0.06
0.04
0.02
0.00
0.00

0.20
0.40
0.60
Number of complaints (/km)

0.80

Figure 11. Relationship between number of complaints andprobability of pavement damages (FY2011)0.12
Probability of pavement damages（/km/1 inspedtion）

Fig.11, fig.12 and fig.13 illustrate sections corresponding complaint and occurrence probability ofpavement damage. “×” overlapped in figures means
S16 having specifically much reliability- Ⅰ and“◇” means S23 – 26 alike. In 2012 and 2013, thetwo results are related to positive correlation. And inevery result, “×” is observed in the rage that X-axis
is high. In 2012 and 2013 “◇” is observed the rangethat X-axis is relatively high.

y = -0.0038x + 0.0196
R = 0.051

FY20120.10

y = 0.1033x + 0.015
R = 0.611

S160.08

S23～S26

0.06

4.3 The relationship between sections indicated bycomplaint and pavement conditions
In order to distill the especially poor part of roadfrom investigation record of pavement condition, wetreat probability of exceeding target value of management as excess probability. Fig.14 and Fig.15 illustrate sections corresponding complaint andIRI/cracks excess probability. (Rutting is not overthresholds.) “×” and “◇” is treated as well asabove. Correlation can’t be observed with fig.14. On

0.04
0.02
0.00

0.20
0.40
0.60
0.80
Number of complaint (/km)
Figure 12. Relationship between number of complaints andprobability of pavement damages (FY2012)

1584

0.00

FY2013S16
S23～S26

0.08
0.06
0.04
0.02
0.00

0.3

2012（S1～S9）
2013（S10～S26）

0.2

S1
S23～S26

0.15
0.1

0.05
0-Central Nippon Expressway Co., Ltd ：Maintenance Inspection Guideline, Jun., 2013
Central Nippon Expressway Co., Ltd：DesignGuideline, 3rd edition, Jul., 2013
The Committee on Pavement Engineering,
JSCE ： Pavement Construction Library 7 –fundamental of pavement construction, Mar.,
2012

0.2
0.4
0.6
0.8
Number of complaints (/km）

1Figure 14. Relationship between number of complaints and excess probability of IRI 2.7

REFERENCES-0.80

2011（S10～S26）

0.25

Excess probability of crack 10%

This study doesn’t include any repairing data following inspection result data and is not analyzed intime-series. In the future work, we are going to add
repairing data and construction types in chronological order.

0.20
0.40
0.60
Number of complaints (/km）

Figure 13. Relationship between number of complaints andprobability of pavement damages (FY2013)06 FUTURE WORKy = 0.0494x + 0.0305
R = 0.452

0.10

0.00

Excess Probability of IRI 2.7

In this study we considered validity of users’ complaints comparing pavement conditions. The results
are following bellow.
The relationship between the inspection surface
condition used for pavement management and usercomplaints is not strong. In respect to Investigationof road surface, road of expressway is managed
properly. However more pavement damages detected by daily visual inspection occur on the roadwhich is under management thresholds. Most users
tend to lodge complaints about damages on pavement like potholes. In addition to this, high reliability complaints based on the fact and are lodged in
the section that occurrence probability of pavement
damages is high.
We concluded bellow by these results above.
Management of road pavement is carried out basedon record of investigation of pavement condition
like IRI. But they tend to lodge complaints about not
roughness of pavement but sporadic damages likepotholes when road users feel in danger. Thus it ispossible to secure the quality of pavement which users seek by to reduce probability of pavement damages, namely to deal with these sporadic damages
appropriately. And we think that expressway management companies can explain doing appropriate
management including customer’s feedback.

Probability of pavement damages（/km/1 inspedtion）

0.12

5 CONCLUTION

0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
02011（S10～S26）
2012（S1～S9）
2013（S10～S26）
S16
S23～S26

0.2
0.4
0.6
0.81
Number of complaints (/km）
Figure 14. Relationship between number of complaints and excess probability of crack 10%

15850