ITARDA 20th WorkShop Report

Characteristics of and countermeasures to fatal accidents caused bylater-stage elderly people driving kei-passenger cars
Tatsuhiko Saegusa, Researcher, Research Division
Overview
There has been a rise in the number of elderly people driving kei-passenger cars (small-sized passenger carsin Japan) in recent years due to the fact that they are highly economical and convenient. This has resulted in
the number of fatal accidents caused by later-stage elderly (elderly people age 75 or older) driving
kei-passenger cars increasing by approximately 2.3-fold over the ten-year period from 2007 to 2016. The
share accounted for by such accidents out of the total number of fatal accidents caused by later-stage elderly
driving four-wheel vehicles has risen to the point where it is roughly equal to that for medium-sized
passenger cars.
Therefore, this study will focus on later-stage elderly driving kei-passenger cars to perform a comparative
analysis with medium-sized passenger cars. Through this, it will clarify the characteristic format of fatal
accidents while also offering recommendations on effective countermeasures for preventing such accidents
via an analysis of their actual conditions.

1. Background and goals
Fig. 1 shows a graph whereby the number of fatal accidents in which the primary party was the driver of apassenger car or truck in 2016 has been converted to a base of 100,000 license holders by age group. This is atechnique that is commonly used in order to show the tendencies of drivers of different age groups to cause
fatal accidents. However, this does not take into consideration factors like the license holder’s driving
frequency or distance travelled, so it must be kept in mind that this does not necessarily represent the fatal
accident rate per volume of traffic on actual roads. Looking at this reveals a U-shape, with high rates among
young people age 19 and under and later-stage elderly age 75 and over, with the figures increasing the older
people get. Conversely, it can be noted that early-stage elderly between the ages of 65 and 74, while alsoclassified as elderly, are not significantly different from the other age groups in terms of their number of such
accidents. Looking at this graph reveals that young people and later-stage elderly have a particularly
pronounced tendency to cause fatal accidents, which is a phenomenon that merits close scrutiny.

20.0

15.6
15.0

10.5

9.8
10.0

6.7

85 and older

Age group of primary party

80 – 84

4.4

75 – 79

65 – 69

60 – 64

55 – 59

50 – 54

45 – 49

40 – 44

35 – 39

30 – 34

25 – 29

20 – 24

0.0

3.5 3.0
3.2 3.0 2.9 3.3 3.4 3.6
2.5

70 – 74

5.1
5.0

19 and underNumber of fatal accidents that occur per 100,000
driver's license holders (accidents)

ITARDA 20th WorkShop Report(Passenger cars + trucks, 2016)

Fig. 1. Number of fatal accidents by age group of the primary party driver (2016)

Next, the rise or fall in the number of fatal accidents will be shown for each age group. Fig. 2 is a graphshowing the trend over the past ten-year period from 2007 to 2016 regarding the number of fatal accidents
where the primary party was the driver of a passenger car or truck. Here, the reader should focus on the factthat while the number of fatal accidents among nearly every age group (including the young) is dropping,
only among the later-stage elderly has this risen from 316 to 395 accidents. As a result, the composition rateof accidents accounted for by the later-stage elderly has risen from 7.0% to 13.5%, nearly doubling over the
past ten years. This is presumably significantly impacted by the rise in the population of later-stage elderly
drivers. Since the population of later-stage elderly drivers is projected to rise in the future, it will be
extremely important that countermeasures against fatal accidents by these drivers be taken in order tocontinue reducing the overall number of fatal accidents still further.

ITARDA 20th WorkShop Report

15.0[VALUE]%

Number of fatal accidents (accidents)[VALUE]%

4,000

670
541

550 447

463

3,000

400 383

10.0
351 353

311

2,000
5.0
1,000

0

316 315 326 351 344 377 372 379 385 395
2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

H19 H20 H21 H22 H23 H24 H25 H26 H27 H28

0.0

Composition rate of drivers age 75 and older (%)

5,000

24 and under
24歳以下
25 – 34
25~34歳35 – 44
35~44歳45 – 54
45~54歳
55 – 64
55~64歳65 – 74
65~74歳
75 and older
75歳以上(Primary party,
passenger cars +trucks)Fig. 2. Number of fatal accidents by age group of the primary party driver (2016)

Next, the trends in the number of fatal accidents will be shown by focusing on the vehicle type to indicate
what later-stage elderly were driving when they caused a fatal accident. Fig. 3 is a graph that indicates thetrends over the past ten-year period from 2007 to 2016 regarding the number of fatal accidents in which alater-stage elderly driver was the primary party by vehicle type. Apparently, there has been a substantial
increase in just the number of fatal accidents involving kei-passenger cars, which rose by approximately
2.3-fold over this ten-year period. The number involving medium-sized passenger cars and kei-trucks(small-sized trucks in Japan) have held largely steady, and so as a result the share of accidents accounted forby kei-passenger cars has increased. In recent years the shares from medium-sized passenger cars andkei-trucks have been largely identical. The reason for this is not because kei-passenger cars have suddenly
become more dangerous, but rather because the number of later-stage elderly people driving kei-passenger
cars has increased. In other words, this can be thought of as having come about due to an increase in thisparameter.

ITARDA 20th WorkShop Report

50.0[VALUE]%[VALUE]%

Other
four-wheel vehicles
その他四輪車Medium-sized
普通乗用 passenger cars

300

94

119 122120 111 118

40.0

101

107 96 115

30.0

200
154 145

133 134 133
141 150

20.0

145 138 140

Kei-trucks
軽貨物

Composition rate (%)

Number of fatal accidents (accidents)

400

Kei-passenger
cars
軽乗用
%
of kei-trucks
軽貨物割合%
of medium-sized passenger cars
普通乗用割合%of kei-passenger cars
軽乗用割合

100
10.0
55

64

62

92

117 124 126
87 102 102

0

0.0
2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

H19 H20 H21 H22 H23 H24 H25 H26 H27 H28(Primary party,
passenger cars +trucks, 75 and older)Fig. 3. Trends in the number of fatal accidents for later-stage elderly as the primary party by vehicle type

Data that suggests this will be introduced here. Fig. 4 shows the trend in the number of owners of four-wheel
vehicles over the past ten years from 2007 to 2016.1) Whereas there has been a slight decrease in the numberof medium-sized passenger cars and kei-trucks over the past ten years, the number of kei-passenger carsalone has risen by roughly 1.4-fold. There are a number of conceivable reasons backing this, such as
kei-passenger cars’ inexpensive maintenance costs and excellent maneuverability, while it is also believed tohave come about as a result of car manufacturers releasing superior products. Fig. 5 shows the compositionby age group for kei-passenger car drivers for the years 2007 and 2015.2) Apparently, the proportion
accounted for by people in their 70s or older has increased, with the average age also shifting upwards from46 to 53 years old. Based on this data we can see that the number of owners of kei-passenger cars isincreasing in and of itself, and that in addition the proportion of later-stage elderly drivers within this is also
increasing. As a result, the number of later-stage elderly driving kei-passenger cars is rising at a rapid pace.
Calculating the number of kei-passenger cars being driven by elderly people to the extent that this can beinferred from this data yields the following results. In 2007 people in their 70s and older owned 7% of the
15.93 million kei-passenger cars owned, while in 2015 they owned 12% of the total of 21.85 million. Thismeans that the number of kei-passenger cars owned by people in their 70s and older rose from 1.12 million
vehicles in 2007 to 2.62 million vehicles in 2015. This corresponds to an increase of approximately 2.3-foldover ten years, which is largely consistent with the pace at which the number of fatal accidents involving
kei-passenger cars driven by later-stage elderly is rising. It is predicted that in the future this will increase at agreater pace than ever before as people in their 60s, a group that includes the baby boom generation, continue
aging.

ITARDA 20th WorkShop Report

4,500

Medium-sized passenger cars

Number of four-wheel vehicles owned(10,000 vehicles)

4,000
3,500
3,000
2,500
Kei-passenger cars

2,000
1,500
Kei-trucks

1,000
Other four-wheel vehicles

500
0

H27

H28
2016

H26

2015

H25

2014

2011

H24

2013

H23

2012

H22
2010

2007

H21
2009

H20
2008

H19

Fig. 4. Trends in the number of owners of four-wheel vehicles

0%

20%

40%

60%

80%

100%
Average age(years)

FY2007

H19年度

17

20

20

22

14

7

46

12

53

n=2121FY2015

H27年度

10

21

19

18

20

n=211420s
and under
20代以下

30s
30代

40s
40代

50s
50代

60s
60代

70s
and older
70代以上

Fig. 5. Changes in kei-passenger car drivers by age group

Given this background, it is possible that the number of fatal accidents caused by later-stage elderly driving
kei-passenger cars will rise even more. Therefore, it will be difficult to further reduce the number of fatal
accidents unless countermeasures tailored to the characteristics of said accidents are taken.
Therefore, this study will clarify the characteristic format of fatal accidents among elderly drivers of
kei-passenger cars and analyze their details in order to offer recommendations on the countermeasuresrequired for reducing the number of fatal accidents in the future.

ITARDA 20th WorkShop Report

2. Analysis of the characteristic format of fatal accidents among later-stage elderly driving
kei-passenger cars
(1) Characteristics of fatal accidents by later-stage elderly driving kei-passenger cars by type of accident
Fig. 6 shows the composition rate of fatal accidents by type of accident for each type of primary party. The
horizontal axis shows the number of accidents by each respective primary party driver type, while the bar
graphs show the ratio of each type of accident in a color-coded manner. First off, this graph reveals
characteristics of accidents by later-stage elderly by comparing later-stage elderly with all of the age groups
when driving the same vehicle type. Compared with all of the age groups, later-stage elderly people arecharacterized by having a lower share of fatal pedestrian-vehicle accidents regardless of the type of vehicle,
but a higher share of fatal accidents from head-on collisions and collisions with roadside structures. The
reason behind this is believed to be because later-stage elderly themselves are more prone to dying when
accidents occur due to their reduced impact tolerance, with this becoming more pronounced with accidents
where the damage to the driver is particularly severe. Next, when we compare later-stage elderly driving
kei-passenger cars with those driving medium-sized passenger cars, a number of characteristics become
apparent. These include the high percentage of head-on collisions with kei-passenger cars, while at the sametime there is virtually no change in the share of collisions with roadside structures and the share ofpedestrian-vehicle accidents is low. In terms of the underlying reason for why these sorts of differences arise,
it is possible that this is impacted by differences in vehicle structure and the drivers’ driving style. But the
precise reason for this is unclear, and further detailed analysis is needed on this. When we compare the total
number of casualty accidents in the same manner, we see that there is virtually no change in the share ofhead-on collisions owing to the vehicle type. Therefore, it is not the case that later-stage elderly driving
kei-passenger cars are particularly prone to causing head-on collisions, but rather when they do cause ahead-on collision it is highly likely to result in a fatal accident. Moving forward, further analysis will be
performed on characteristic fatal head-on collision accidents involving kei-passenger cars driven bylater-stage elderly.

Primary party driver
All ages
75 and over

ITARDA 20th WorkShop ReportKei-passenger
cars 軽乗用
n = n=924件
924 accidents
Medium-sized
普通乗用passengercars
n = n=1,099件
1,099 accidents
Kei-passenger
cars 軽乗用
n = n=8,206件
8,206 accidents
Medium-sized
普通乗用passengercars
n =n=14,807件
14,807 accidents

26.2%

22.3%

25.7%

14.9%

15.2%

10%

Head-on
正面衝突
collisions

23.6%

15.4%

10.8%

0%

18.9%

39.8%

15.8%
20%

30%

Angle
出会い頭
collisions

Vehicle-vehicle

40%
Other
その他

50%

42.1%
60%

70%

Collisions
with
工作物衝突
roadside
structures

80%
Other
その他

90%

100%

Pedestrian-vehicle
人対車両
accidents

Single vehicle(Total from 2007-2016) Excluding train accidents

Fig. 6. Composition rate of fatal accidents by type of accident and type of primary party(2) Case fatality rates for head-on collisions by model year of kei-passenger cars
To offer a glimpse of the changes in collision safety for kei-passenger cars during head-on collisions, Fig. 7
shows the case fatality rates for drivers as viewed by different kei-passenger car model years for head-on
collisions. Here, the case fatality rate will be defined as the ratio of the number of fatalities to the number ofcasualties out of the total number of drivers who got into an accident. The bar graphs each show the casefatality rates for all ages and for people age 75 and older, with the horizontal axis showing the vehicle modelyear. This has been divided up into three periods: 1998 and earlier, 1999 – 2008, and 2009 – 2016. In general,the case fatality rate tends to be lower the newer the model year becomes. A variety of different measures
have been taken to bolster the collision safety performance of kei-passenger cars, such as enhancing theircollision safety standards via regulatory revisions and crafting legislation for offset frontal collisions.
Therefore, it can be surmised that the results of these are surfacing. Yet the case fatality rate remains higher
among later-stage elderly compared with that for all ages. The hope is that further improvements will bemade when it comes to collision safety. But it will still be no easy feat to protect later-stage elderly, who haverelatively low impact tolerance when accidents do occur. Therefore, it will become increasingly important toenhance preventative safety measures for preventing collisions in the future.

ITARDA 20th WorkShop Report

14.0
All ages
全年齢75
and older
75歳以上

Case fatality rate (%)

12.0
1998
Kei-vehicle
regulations
revised toenhance collisionsafety standards

10.0
8.0
6.0

2007
Legislation
crafted for
offset frontal
collisions

4.0
2.0
0.0
1998
and earlier
H10以前

H11~201999– 2008
Vehicle model year (year)

H21~282009– 2016* Case fatality rate = No. of fatalities ÷ No. of casualties ×100%(Primary + secondary parties, wearing seatbelt, total from 2007-2016)

Fig. 7. Case fatality rates by vehicle model year for kei-passenger car drivers (head-on collisions)(3) Analysis of the actual conditions of fatal head-on collision accidents caused by later-stage elderly driving
kei-passenger cars
In this section, analyses will be performed on when, where, and why later-stage elderly driving kei-passenger
cars caused fatal head-on collision accidents in the interest of prevention and safety. For the analyses, thetotal figures for the number of fatal accidents over the past ten years was used in which the primary party wasa kei-passenger car driver aged 75 and older and drivers of the same in all ages for purposes of comparison,
as well as drivers of a medium-sized passenger car age 75 and older and drivers of the same in all ages, witha four-wheel vehicle as the secondary party.

[1] When do fatal head-on collision accidents occur?
Fig. 8 shows the composition rate of fatal head-on collision accidents by time period. When you compare
accidents between two drivers age 75 and older and between two drivers of all ages, there is virtually no
difference in the trends for any of these based on the type of vehicle. Conversely, when drivers age 75 andolder are compared with drivers of all ages their trends diverge, with those age 75 and older getting into an
extremely large number of accidents in the daytime and a small number in the early morning and at nightcompared with all of the age groups. The reason for this is because with drivers of all ages there is variance inthe time periods in which accidents occur as a result of people commuting to and from school and work in themorning and evening, as well as driving at night. As opposed to this, it is conjectured that later-stage elderly
people have few opportunities to go out by car in the early morning and at night, with their driving
concentrated in the daytime. This is not limited to just head-on collisions, but is a trend that is noted withaccidents in general caused by later-stage elderly drivers.

ITARDA 20th WorkShop Report

Composition rate of fatal accidents (%)

25.0

75 and older
75歳以上

n = 203 accidents
75 and older
75歳以上

20.0

n = 159 accidents
All ages
全年齢

n = 1,174 accidents
All ages
全年齢

15.0

n = 1,456 accidents

10.0

5.0

0.0
0~1
0-2

2~3
2-4

4~5
4-6

6~7
8~9 10~11
18~19 20-22
20~21 22~23
6-8 8-10
10-12 12~13
12-14 14~15
14-16 16~17
16-18 18-20
22-24
Times when accidents occur (hour unit)(Versus four-wheel vehicle secondary party, head-on collisions, total from 2007 - 2016)

Fig. 8. Composition rate of fatal accidents by time period (head-on collisions)[2] Where do fatal head-on collision accidents occur?
Next, the types of locations where fatal head-on collision accidents occurred will be analyzed. Fig. 9 shows
the composition rate of fatal head-on collision accidents by topography. There are virtually no differences inthe trends shown in the graph by type of vehicle or age, but it does show that nearly 80% occur in non-urban
areas where there are few homes and structures. There are some cases where differences arise by topography
based on the type of accident, but since there is no difference with this for head-on collisions it is possiblethat these occur in similar sorts of locations for all drivers. Fig. 10 shows the composition rate of fatal
head-on collision accidents based on the collision site. Collision sites have been divided up into thoseoccurring within the oncoming traffic lane and other, with “other” here taken to include those in Lane 1, atintersections, in parking lots, and so on. There are virtually no differences in the trends shown in the graph bytype of vehicle or age, but it does show that more than 70% of the collisions took place in the oncoming
traffic lane. Since collisions in the oncoming traffic lane can only occur if a driver goes over the center line,
these presumably must have all involved a driver deviating from their lane. Moreover, viewing a breakdownof this by road alignment within the oncoming traffic lane ultimately showed that a slightly larger number
occurred along curved road sections for all drivers. Therefore, the typical head-on collision could be said tobe a case in which there is a collision with an oncoming vehicle resulting from a driver deviating from theirlane at a curved road section.

ITARDA 20th WorkShop Report

Composition rate of fatal accidents (%)

100%
Urban areas –市街地 -人口集中
concentrated
population
Urban
areas
–
Other
市街地 -その他

90%
80%

Non
-urban areas
非市街地

70%
60%
50%
40%

77.1%

77.3%

78.6%

78.3%

30%
20%
10%
0%

n = 1,456 accidents n = 1,174 accidents n = 159 accidents n = 203 accidents
Medium-sized
passenger cars

Kei-passenger
cars

Medium-sized
passenger cars

Kei-passenger
cars

75 and older

All ages(Versus four-wheel vehicle secondary party , head-on collisions, total from 2007 - 2016)

Fig. 9. Composition rate of fatal accidents by topography (head-on collisions )Composition rate of fatal accidents (%)

100%
Other
その他

90%
80%

Oncoming
対向車線traffic(直線lane) (straight)

70%

Oncominglane)(curved)
対向車線traffic
(カーブ

60%

35.0%

36.1%

39.9%

39.5%

50%

33.3%

34.5%

40%
30%
20%

37.7%

40.9%

10%
0%

n = 1,456 accidents n = 1,174 accidents n = 159 accidents
Medium-sized
passenger cars

Kei-passenger
cars

All ages

Medium-sized
passenger carsn = 203 accidents

Typical head-on collisionKei-passenger
cars

75 and overcollisions, total from 2007 - 2016)(Versus four-wheel vehicle secondary party, head-on collisions,Fig. 10. Composition rate of fatal accidents by collision site (head-on collisions )Next, the sorts of roadways on which fatal head -on collision accidents occurred will be indicated. Fig. 11

indicates the composition rate of fatal head-on collision accidents involving a kei-passenger car where theITARDA 20th WorkShop Reportprimary party is a driver age 75 or older by road width and route type. Apparently, such accidents areconcentrated on nonnon--intersection
intersection roads between 5.5m and 9m, as well as main roadways such as national
highways and principal local roads (but excluding expressways). Moreover, when road width / size and theconsideration, then presumably the majority oftrends with collision sites mentioned above are taken into consideration,
singlengle-lane in one direction.
direction. What is not shown here,
these accidents occurred along general roadways with si
however, is that since similar tendencies are seen with other drivers this is considered to be a characteristic ofhead-on collision accidents in general.

(Primary party age 75 or older, kei-passenger vehicle)

50.0[VALUE] %

40.0
30.0

National
highway
国道
Principal
local road
主要地方道

20.0

Prefectural
road
都道府県道
Municipal
市町村道road

10.0

Expressway
高速道路

Other
その他
Intersection

13m orwider

9 – 13m

5.5 – 9m

0.0
Less than
5.5m

Composition rate of fatal accidents (%)[VALUE] %n = 203 accidents

Road width(Versus four-wheel vehicle secondary party, head-on collisions,collisions , total from 2007 - 2016)

Fig. 11. Composition rate of fatal accidents by road width × route type (head-on collisions )[3] Why do fatal head-on collision accidents occur?
Next, the causes behind the occurrence of fatal head -on collision accidents will be analyzed from theperspective of human factors. Fig. 12 shows the composition rate of fatal head-on collision accidents byhuman factor. According to the graph, steering error accounts for roughly 20%, judgement errors account forroughly 15%, and failure to pay attention forward (which includes distracted driving, adjusting radio /chatting, dozing off, being lost in thought, etc.),etc.) , account for about 50%. At the same time, the breakdown for
the failure to pay attention forward category varies by driver. The tendency observed with drivers age 75 andolder over all ages, as well as with those in kei-passenger cars more so than those in medium -sized passengerlower
er proportion of drivers dozing off while driving and a higher proportion that engaged incars, was for a low

ITARDA 20th WorkShop Reportaimless driving, such as by getting lost in thought. This is nothing more than conjecture, but this could
conceivably be because later-stage elderly driving kei-passenger cars in particular have frequent occasion todrive down roads they are used to traveling down for relatively short periods of time, so while they do notreach the point of dozing off they do tend to engage in absentminded driving.

90%

Other
その他

80%

21.1%

22.5%

19.9%

21.3%

70%
60%

Judgment error
判断の誤り

12.0%

30%

16.9%

15.4%

Distracted driving
脇見運転

14.2%

8.8%

13.0%

ラジオ/雑談等
chatting, etc.

5.9%

Dozing off while
居眠り運転

12.5%

11.0%

15.0%

50%
40%

Adjusting radio /

13.5%

0%

driving

Lost in thought,
考え事等

14.9%

etc.

20%
10%

Steering error
ハンドル操作不適

30.9%

27.9%

21.4%

34.3%

Filure to pay attention forward

Composition rateof fatal accidents (%)

100%

n = 1,316 accidents n = 1,004 accidents n = 136 accidents n = 169 accidents
Medium-sized
passenger cars

Kei-passenger
cars

Medium-sized
passenger cars

All ages

Kei-passenger
cars

75 and older(Versus four-wheel vehicle secondary party, head-on collisions, total from 2007 - 2016)
Excluding cases that could not be investigatedFig. 12. Composition rate of fatal accidents by road width × route type (head-on collisions)[4] Summary of the analyses of actual conditions
Based on the results of the analyses thus far, we have learned that a high percentage of fatal head-on collision
accidents are characterized by involving a later-stage elderly driver driving a kei-passenger car. However,looking at the largest number of cases of when accidents occur indicates that while characteristic differences
for later-stage elderly can be seen based on the time period, there is no noticeable difference between themand others in terms of where accidents occur, their collision site, or their cause. As such, it appears that any
driver can cause a fatal head-on collision accident in similar sorts of settings. Therefore, the assumption isthat satisfactory results with reducing accidents can be expected by further enhancing commonly-envisaged
preventative measures for head-on collision accidents.

ITARDA 20th WorkShop Reportpreca utionary measures for head-on collisions
3. Considering examples of precautionary[1] Examples of infrastructure-based precautionary measures for head-on collisions

Based on the analytical results, the effectiveness of a number of general preventative measures for head-on
collision accidents will be considered. To start with, examples of infrastructure-based countermeasures tothese will be shown. Fig. 13 shows an example of a high visibility road marking. Since these road markings

contain intermittent protrusions, they are believed to be effective at preventing drivers from deviating fromtheir lane due to failure to pay attention forward by producing a noise or vibration when tires pass over them.
These road markings were originally developed with the goal of improving visibility at night and during rainy
weather by using glass beads within the paint film itself to set up protrusions so that they are not submerged
when it rains. For this reason, such road markings are described as “high visibility.” On the other hand, Fig.

14 shows a center line that is called a rumble strip. 3) The aim with these is to effectively prevent drivers fromdeviating from their lane in a similar manner through the installation of indents in the road rather thanprotrusions. Having protrusions like those in Fig. 13 presents an obstacle for snow removal, and so these haveprimarily been adopted mainly in regions that experience snowfall. Soundly installing and managing these
sorts of center lines will serve as an important countermeasure against accidents, particularly for major
roadways with single-lane in one direction in non -urban areas.

Fig. 13. A high visibility road marking

ITARDA 20th WorkShop Report

Fig. 14. A rumble strip[2] Examples of vehicle-based preventative measures for head-on collision accidents

shown.. Fig. 15 is an image
Next, vehicle-based preventative measures for head -on collision accidents will be shownof a lane-deviation warning system. These are systems that mainly use cameras mounted on the vehicle todetect lanes and issue a warning when it looks like the vehicle is about to deviate from its lane. According toechnology, in 2015 such systems werea survey on the dissemination status of Advanced Safety Vehicle Technology,
equipped on approximately 18% of new vehicles ,4) showing that they are gradually becoming morewidespread. In addition, in recent years systems that not only make a noise but also cause the steering wheel
to vibrate at the same time have begun to be practically implemented. Meanwhile, Fig. 16 is an image of alane-deviation control system. The major difference between these and the warning systems is that thesesystems will intervene in the steering and braking in order to assist the driver in returning to their originallane. It is surmised that these sorts of systems will be effective at combatting accidents caused by operating
errors.
These systems were still only equipped on a small number of vehicle models as of 2017. But in recent years

systems that come equipped on compact cars and kei-motor vehicles have begun to appear, with the
expectation being that they will spread still further.
Yet there are cases where both of these systems fail to function normally on account of the conditions, so
caution is required. For example, it is known that in cases like when the weather is bad or when the centerline is blurry it can make it difficult for the camera to detect this. Moreover, it is envisioned that these sorts ofsystems will ordinarily operate when travelling at high speeds, and so at times they fail to operate during
low-speed travel.

ITARDA 20th WorkShop Report

Warning
15. Image of a lane -deviation warning system
Fig. 15.

Steering assistanceFig. 16. Image of a lane -deviation control system[3] Proposed improvements for lane-deviation prevention devices

Described below is a way to improve these lane-deviation prevention devices based on the precautions
raised above. Fig. 17 shows the composition rate of fatal accidents by the danger perception speed of the
primary party
party.. It reveals that most of these accidents occur at speeds of less than 60km/h, regardless of thevehicle type or driver’s age. For kei-passenger cars driven by drivers age 75 or older in particular, theresponses peak in the 40km/h-range at about 43%, followed by the 30km/h-range at about 25%, with theseconcentrated at moderate to low speeds. For this reason, installing systems that operate not just at high speeds,
but at moderate and low speeds of less than 60km/h , in order to prevent head-on collision accidents could
potentially reduce an even greater number of fatal accidents.

ITARDA 20th WorkShop ReportOver
80km/h- 80km/h- 70km/h- 60km/h- 50km/h- 40km/h- 30km/h- 20km/h- 10km/hComposition rate of fatal accidents (%)

All ages, Medium + kei-passengercars
n = 2,493 accidents
75 and older,
Kei passenger cars
Kei-passengern = 191 accidents

Danger perception speed of primary party(Versus four-wheel vehicle secondary party, head-on collisions, total from 2007 – 2016)
Excluding cases that could not be investigatedFig. 17. Composition rate of fatal accidents by danger perception speed of the primary party(head -on collisions)

4. Conclusion
This analysis revealed that countermeasures against head-on collision accidents involving kei-passenger cars,

especially preventing deviations from one’s lane, are important for the sake of reducing the number of fatal
accidents caused by later-stage elderly drivers. The hope is that road administrators will maintain and manageroad
ad shoulders in order to accomplish this. There are two main reasons for this: because
center lines and ro
having uneven surface conditions will prevent drivers from deviating from their lanes, and because it will
boost detection by onboard cameras. For car manufacturers
manufacturers,, it is hoped that they will popularize and enhancelane-deviation prevention devices equipped on all of their vehicle models, including kei -passenger cars. It isalso hoped that systems that operate even at moderate and low speed
speedss of less than 60km/h will be further
enhanced in the future.

Reference1) 日本自動車工業会：自動車保有台数統計資料

四輪車の使用特徴調査報告書の使用特徴調査報告書」」,2016 年 3 月
2) 日本自動車工業会：「2015 年度 軽四輪車
「新しい事故対策手法としてのランブルストリップスの開発と実用化に
3) 寒地土木研究所 平澤他：
関する研究」，土木学会論文集 第４部門 NO.800 / Ⅳ－69，2005 年 10 月．
国土交通省：ASVASV 技術普及状況調査資料4) 国土交通省：