ITARDA 26th Work Shop Report2023
26th Presentation Session for Traffic Accident Investigations, Analysis, and Research

Identification of locations where accidents frequently occur using data on accidents
involving property damage data and analysis of accident patterns

Toshio Yamamoto
Investigator, Research Section II, Research Division

1

ITARDA 26th Work Shop Report

1. Introduction
The number of fatal accidents nationwide in Japan peaked in 2004 level at 952,720. Subsequently, as a result oftraffic safety measures taken by organizations, such as those involved in public safety, road construction, andautomobile manufacturing, the number of casualty accidents has been on a downward trend, decreasing to 300,839

1,400,000

Number of deaths (1992) 11,452

1,200,000

Peak number of injuries (2004)

14,000Peak number of casualty
accidents (2004)

12,0001,000,000

10,000800,000

8,000

600,000

6,000

400,000

4,000

200,000

2,000

0Number of deaths (persons)

NumberNumberofofcasualty
casualtyaccidents
accidents(accidents)(accidents)
Numberofofinjuries
injuries(persons)(persons)
Numberas of 2022, or approximately 30% of the 2004 peak (see Fig. 1).

0
H1 H3 H5 H7 H9 H11 H13 H15 H17 H19 H21 H23 H25 H27 H29 R01 R03
Number ofcasualty accidents

Number ofinjuries

Number ofdeaths

Despite this nationwide decrease in casualty accidents, a traffic white paper issued by the Ibaraki Prefectural
Police has shown that accidents involving property damage had been on an upward trend until 2018 (see Fi g. 2).
(accidents)
100,000（件）80,00060,00040,00020,0000

H20 H21 H22 H23 H24 H25 H26 H27 H28 H29 H30
Property damage
物損
⼈⾝Casualty
全事故

R01

R02R03Total accidents

Fig. 2 - Trends in casualty accidents and accidents involving property
damage in Ibaraki Prefecture
Because accidents involving property damage could potentially turn into casualty accidents depending on thecircumstances, any increase in such accidents is undesirable, and it is extremely important to identify accident-prone
areas using data on accidents involving property and conducting accident analysis.
Therefore, in this study, I utilized database of accidents involving property damage (approx. 300,000 accidentsfrom 2015 to 2018) provided by the Ibaraki Prefectural Police in order to conduct the following:(1) Macro analysis aimed at assessing the characteristics of accidents involving property damage by1

ITARDA 26th Work Shop Reportcomparing them with casualty accidents(2) Identification of locations where accidents involving property damage frequently occur using aGeographic Information System (GIS)(3) Accident pattern analysis of locations where accidents involving property damage frequently occur
2. Macro analysis
Macro analysis was performed by comparing the details of accidents involving property damage with casualty
accidents in terms of road type, road shape, accident type, and time of occurrence.
2-1. Road type
When comparing the percentages of accidents that occurred on expressways, national highways, major prefecturalroads, and prefectural roads (hereinafter collectively referred to as “trunk roads”) with those that occurred on local
municipal roads (hereinafter referred to “community roads”), I found that most casualty accidents occurred on trunkroads (trunk roads: 57%, community roads: 38%), while
accidents involving property damage occurred almost
equally on both types of roads (trunk roads: 38%,community roads: 34%). Furthermore, I found that 24%of accidents involving property damage took place inAccidents
involving
物損事故 2% 17%
property
damageCasualty
⼈⾝事故 1%
accidents

locations such as parking lots (referred to as “location ofgeneral traffic” in accident reports), indicating that more
accidents

involvingproperty

damageoccuroncommunity roads and parking lots than do casualty

19%

34%

29%

0%

24% 4%

28%

20%

40%

38%

4%1%

80%

100%

60%

National highways
⼀般国道
Local municipal roads
Major主要地⽅道及⼀般県道
prefectural roads & Prefectural roads ⼀般市町村道
Other
Parkinglots, etc.
駐⾞場等
その他
Expressways(incl. limited-access roads)
⾼速道路（含む⾃専道）

Fig. 3 - Percentages by Road Type (2015 to 2018)

accidents.
2-2. Road shape
When comparing the percentages of accidents
involving property damage and casualty accidents that
occurred at intersections or near intersections (hereinafterreferred to “intersections, etc.”) with those that occurredAccidents
involving
物損事故
propertydamage0.00322%

16%

31%

31%

at non-intersections, I found that 52% of casualty
accidents occurred at intersections, etc. and 43% occurred

0.000

Casualty
⼈⾝事故accidents

35%

17%

43%

5%

at non-intersections, while 38% of accidents involving
property damage occurred at intersections, etc. and 31%
at non-intersections. On the other hand, when comparing
the percentages of accidents that occurred at intersections
with those that occurred near intersections, I found that

0%

20%

40%

Intersections
Near intersections
交差点交差点付近
Non-intersections

60%

80%

100%

Railroad crossings
Parking lots, etc.

単路踏切

駐⾞場等

Fig. 4 - Percentages by Road Shape (2015 to 2018)

35% of casualty accidents occurred at intersections while
17% occurred near intersections for a ratio of nearly 2:1. In the case of accidents involving property damage, I foundthat 22% occurred at intersections while 16% occurred near intersections for a ratio of nearly 2:1.5, indicating that
accidents involving property damage occur more frequently near intersections.
2ITARDA 26th Work Shop Report2-3. Accident type
Although rear-end collisions accounted for nearly 40%
property damage, I found that rear-end collisions, crossing

1%
Accidents
involving
物損事故 1% 22%
property
damagecollisions, and vehicle-vehicle accidents, etc., each3%of casualty accidents, in the case of accidents involving

accounted for roughly 20% of all accidents. I also

Casualty
⼈⾝事故
accidents

0%
17%

26%

0%
43%

9%

33%

25%

19% 1%

observed that single-vehicle accidents accounted for the0%largest proportion of accidents involving property damage

40%

Pedestrian-vehicle
⼈対⾞両accident
Rear-end追突 collision
Vehicle-vehicle
⾞両相互その他
accident, etc.
Otherthan the above
上記以外

at 33%. It can be assumed that the high number of singlevehicle accidents is due to any collision with a parked
vehicle in a parking lot being considered a single-vehicle
accident.

20%

60%

80%

100%

Head-oncollision
正⾯衝突
Crossing
collision
出会い頭Single-vehicle
⾞両単独 accident

Fig. 5 - Percentages by Accident Type (2015 to 2018)

2-4. Time of occurrence

12%

damage, the same trend has been

10%

observed in which most such accidents

8%occurschool6%commuting hours in the morning and4%evening.

2%

accidents

duringinvolvingworkandDuring work and school commuting
hours, the percentage of casualty
accidents is slightly higher than that ofaccidents involving property damage,while

duringmid-day

hours,

the0%

1 AM
1時台
2 AM
2時台
3 AM
3時台
4 AM
4時台
5 AM
5時台
6 AM
6時台
7 AM
7時台
8 AM
8時台
9 AM
9時台
10 AM
10時台
11 AM
11時台
12 PM
12時台
1 PM
13時台
2 PM
14時台
3 PM
15時台
4 PM
16時台
5 PM
17時台
6 PM
18時台
7 PM
19時台
8 PM20時台
9 PM
21時台
10 PM
22時台
11 PM
23時台

property

and12AM
0時台

In the case of both casualty accidents

involving property damage
Casualty accidents
⼈⾝事故 Accidents
物損事故

Fig. 6 - Percentages by Time of Occurrence

percentage of accidents involving property damage is higher than that of casualty accidents.
3. Identifying locations where accidents involving property damage frequently occur
During this research, I worked to identify intersections where accidents involving property damage frequently
occur by using the coordinate data from the database for accidents involving property damage together with GIS.
Our general concepts regarding this identification method are:(1) If within the circle of an arbitrary radius centered on the location of a given accident (referred to as the“frequent occurrence criteria”), a certain number of accidents involving property damage have occurred nearby(referred to as the “concentration criteria”), that circle is set aside for further investigation.
(see Fig. 7)(2) The same process is performed for all accidents involving property damage. (see Fig. 7)(3) If any of the circles set aside for further investigations overlap, the outer circumference of each circle shall bein the same location. (see Fig. 8)
3

ITARDA 26th Work Shop Report

By examining combinations of concentration criteria (radius of circle) and frequent occurrence criteria (numberof accidents involving property damage within the circle), the concentration criteria (radius) suitable for identifying
intersections was 10 m while the frequent occurrence criteria was 30 accidents.

Fig. 7 - Image of circles (blue) set aside for furtherFig. 8 - Image of locations identified as having

investigation

frequent accidents involving property damage

Using these identification criteria (concentration criteria: 10 m radius, frequent occurrence criteria: 30 accidents),
I were able to identify a total of 29 locations, including 16 intersections and 13 parking lots.
Accident pattern analysis was then conducted on these identified intersections where accidents frequently occur(16 intersections).
4. Accident pattern analysis of locations where accidents involving property damage frequently occur
4-1. Overview of locations where accidents frequently occur
When classifying these sixteen intersections by roadtype, nine intersections were located on trunk roads, while
the remaining seven were located on community roads.
When further classified by whether these intersections had
a traffic signal or not, I found that two of the intersections
had traffic signals, while the remaining 14 intersections
did not (of these, two of them had only single-light traffic
signals). (see Table 1)

4

Trunk road
Trunk × Trunk
Trunk ×Community
Communityroad
Community ×Community

No. ofintersections

Presence of traffic signal

9 locations

No traffic signal (7 locations)Traffic signal (2 locations)

7 locations

No traffic signal (7 locations)

Table 1. Intersections where accidents involving
property damage frequently occur (16 intersections)

ITARDA 26th Work Shop Report

I also used GIS to identify casualty accidents thatcollate the numbers of casualty accidents andaccidents involving property damage. (see Fig. 9)
Because the number of casualty accidents that
occur at intersections on community roads tends to

Number of accidents involving
property damage (accidents)

accidents frequently occur, which enabled me to80

物損事故件数

had occurred at the identified locations where60
4020（件）be lower, they are considered potential locations for

00

10Intersection

交差点（幹線道路）(trunk roads)

so-called latent casualty accidents. Conversely,

20

Number of casualty
accidents（件）(accidents)
⼈⾝事故件数Intersection
交差点（⽣活道路）(communityroad)

Parking
駐⾞場
lot,
etc.

when looking at the numbers of casualty accidents

Fig. 9 - Numbers of casualty accidents and accidents

that occur at intersections on trunk roads, it can be

involving property damage at the identified 29 locations

seen that these are locations where both accidents involving property damage and casualty accidents frequently
occur.
4-2. Accident pattern analysis
When conducting accident pattern analysis on intersections located on community roads, I analyzed intersections
without traffic signals at which 36 accidents involving property damage and three casualty accidents had occurred.
When analyzed by accident type, crossing collisions accounted for roughly the same amount of casualty accidents
and accidents involving property damage. However, all of the casualty accidents involved a bicycle as the secondary
party, while only seven of the 36 accidents involving property damage involved a bicycle. This leads me to feel thatmeasures aimed at preventing bicycle-related accidents at these same locations are necessary.
When conducting accident pattern analysis on intersections located on trunk roads, I analyzed intersections
without traffic signals at which 59 accidents involving property damage and 12 casualty accidents had occurred.
When analyzing these intersections by accident type, I found that all casualty accidents had occurred due to rearend collisions near the intersections. And, although a large number of the accidents involving property damage atthese intersections were also due to rear-end collisions, crossing collisions were also responsible for three of theseaccidents, indicating that accidents involving property damage occurred within intersections at a different frequency
than casualty accidents.
This leads me to feel that measures aimed at preventing accidents caused by crossing collisions at these same
locations are necessary.
5. Summary
This research using data on accidents involving property damage enabled the following results to be obtained:• I was able to use macro analysis to organize the characteristics of accidents involving property damage bycomparing them with casualty accidents.
• I was able to construct methods of identifying intersections where accidents frequently occur by using
coordinate data for accidents involving property damage together with GIS.
• Through accident pattern analysis performed on intersections where accidents involving property damage
frequently occur, I was able to understand how these accidents occur in a different manner than casualty
accidents, enabling me to identify possibly useful countermeasures.
5

ITARDA 26th Work Shop Report<Acknowledgment>This research was carried out using the database of accidents involving property damage provided by the Ibaraki
Prefectural Police Headquarters. For this, I would like to express our sincere gratitude.
<Source>
Ibaraki Prefectural Police Headquarters Traffic White Paper (2021 Edition)https://www.pref.ibaraki.jp/kenkei/a02_traffic/archives/white_paper/white_paper_r03.html

6