ITARDA 21th WorkShop Report

Current status of motorcycle accidents and emergency transport
Shinji Hamada, Senior Researcher, Research Division

1. Purpose of the study
The conditions surrounding motorcycles and motorcycle accidents have been undergoing a drastictransformation in these past few decades. This is thought to have been backed by a number of factors,
including: (1) the decline in the population of young people, (2) the diversification in people’s interests,and (3) the adoption of motorcycling as an interest by middle-aged and elderly people.
In light of the above, there are calls for the enactment of different traffic measures than those enacted
in the past. Conceivable examples of this would include revising countermeasures against motorcycle
gangs comprised mainly of minors (lifting entry restrictions to downtown urban areas) and awarenessraising activities for middle-aged and elderly return riders who are taking up motorcycling again after
an absence (with measures including rechecking of any decline in their capabilities, etc.). Among these
one can glimpse measures that are being handled, even if only in a partial manner.
This paper will reaffirm the changes in motorcycle accidents and their recent conditions andcharacteristics, thereby clarifying the orientation for traffic measures and getting the word on this out
to the public that will serve to provide backup in promoting effective traffic measures.
One recent initiative begun by the Institute for Traffic Accident Research and Data Analysis (hereafter
abbreviated as ITARDA) is an attempt to develop traffic analyses based on a new approach ofcombining the various traffic accident data possessed by ITARDA with other data (national
geographical information, emergency transport information, etc.).
This paper will use emergency transport data obtained via the Fire and Disaster Management Agency(FDMA) at the beginning of the fiscal year and match this with individual data found amongst the dataon motorcycle accidents. This was done in an attempt to engage in new analyses and deduce problems
that were not possible with past analyses. Some of this will be introduced to the reader, albeit in theform of small tidbits of information.

2. Changes in and the current status of motorcycle accidents
This section lays out the changes in the status of motorcycle accidents since 1990, mainly with regard
to accidents by age group and type of motorcycle.
2.1 Changes in the number of traffic accident fatalities (1990 - 2017)
To begin, the changes in the number of traffic accident fatalities will be discussed by condition. The
phrase “by condition” refers to the conditions present when the accident occurred. In this paper said
conditions will be broadly classified into “while riding in a four-wheel vehicle,” “while riding on a
motorcycle,” “while riding on a bicycle, etc.” and “while walking.” The phrase “bicycle, etc.” usedhere includes motor-assisted bicycles and so forth.

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ITARDA 21th WorkShop Report

While riding in afour-wheel vehicle

While riding on a
motorcycle

While walking

Total

2016

2014

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

Composition rate formotorcycles (%)

Number of fatalities (people)

Fig. 1 shows trends in the number of traffic accident fatalities for each type of condition (1990 - 2017).

While riding on abicycle, etc.
Composition rate formotorcycles

Fig. 1. Trends number of traffic accident fatalities for each type of condition (1990 - 2017)

The number of fatalities for all conditions over the 27-year period from 1990 to 2017 came to 3,694
people, falling by 7,533 from 11,227 (△67.1%). The period around 1990, which is referred to as the“Second Traffic War,” saw a number of traffic accident fatalities in excess of 10,000 people. However,it has fallen since then, to the point of dipping below 4,000 people. This is believed to have come about
as a result of measures against traffic accidents and the dissemination of safety technologies on
vehicles.
The number of fatalities while riding in a four-wheel vehicle over the 27-year period from 1990 to2017 came to 1,221 people, falling by 3,280 from 4,501 (△72.9%). While this was the condition withthe greatest number of fatalities up through 2007, from 2008 onward it fell to second place behindfatalities while walking.
The number of fatalities while riding on a motorcycle over the 27-year period from 1990 to 2017 cameto 632 people, falling by 1,860 people from 2,492 (△74.6%). This is the greatest rate of decrease overthis 27-year period seen among the four types of conditions discussed in this paper. Looking at trends
in the composition rate for the number of fatalities while riding on a motorcycle as a proportion of allof the conditions reveals that this was slightly higher around the year 1990 at around 20%. Yet while ithas since decreased, this condition has not seen any extreme changes, as it has hovered between 15 20%.
The number of fatalities while riding on a bicycle, etc. over the 27-year period from 1990 to 2017 cameto 486 people, falling by 690 people from 1,176 (△58.7%). This remains the condition with the fewest
number of fatalities out of the four types of conditions.
The number of fatalities while walking, over the 27-year period from 1990 to 2017 came to 1,347
people, falling by 1,695 people from 3,042 (△55.7%). Of the four types of conditions discussed in thispaper, this one had the smallest rate of decrease over this 27-year period. Moreover, this was the2

ITARDA 21th WorkShop Reportcondition with the second highest number of fatalities up through 2007 after the condition of whileriding in a four-wheel vehicle. But since 2008 it has remained the condition with the highest numberof fatalities.
If we were to summarize the above findings, the claim could be made that the number of fatalities
while riding on a motorcycle is similar to those from the other conditions in that they have been
trending downward over these past few decades. It could also be said that its composition rate out of
all of the conditions has not changed significantly.
2.2. Changes in the number of fatalities while riding a motorcycle by age group (1990 - 2017)
Next, we will take a look at trends in the number of fatalities while riding on a motorcycle by age
group. Age groups were divided up into seven ranges, including the ages of “16 - 24,” 25 - 34,” up to“75 and older.” The reason that people age 16 and older were made the focus of this study is because
16 years old is the established minimum age at which one can obtain a license for a motor-assisted
bicycle or standard motorized two-wheel vehicle.
Fig. 2 shows trends in the number of fatalities by age group (1990 - 2017).

2016

2014

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

Number of fatalities (people)

Composition rates foreach age group (%)

16 - 24

25 - 34

35 - 4445 - 54

55 - 64

65 - 74

75 and older

16 - 24

35 - 54

65 and older

Fig. 2. Trends in the number of fatalities by age group (1990 - 2017)

The number of fatalities among people age 16 - 24 over the 27-year period from 1990 to 2017 came to
115 people, falling by 1,300 people from 1,415 (△91.9%). This accounts for 69.9% of the total decrease
for motorcycles as a whole. As such, the decline in the number of fatalities while riding on a motorcycle
could be claimed to have been largely attributable to the decline in the number of fatalities amongpeople age 16 - 24.
The number of fatalities among people age 25 - 34 over the 27-year period from 1990 to 2017 came to77 people, falling by 137 people from 214 (△64.0%). However, the number of fatalities for this grouppeaked at 284 people in 2002. So compared with the fact that the number of fatalities among people
age 16 - 24 has continued to decline since peaking in 1990, it followed this same trajectory more than3

ITARDA 21th WorkShop Reportten years later.
The number of fatalities among people age 35 - 44 over the 27-year period from 1990 to 2017 came to
80 people, falling by 43 people from 123 (△35.0%). However, the number of fatalities for this grouppeaked at 149 people in 2004. So compared with the fact that the number of fatalities among people
age 16 - 24 has continued to decline since peaking in 1990, it followed this same trajectory even later
than the 25 - 34-year-old group did.
The number of fatalities among people age 45 - 54 over the 27-year period from 1990 to 2017 came to
133 people, falling by 8 people from 141 (△5.7%). However, this has begun trending upward once
again after bottoming out at 81 people in 2005.
The number of fatalities among people age 55 - 64 over the 27-year period from 1990 to 2017 came to88 people, falling by 117 people from 205 (△57.1%).
The number of fatalities among people age 65 - 74 over the 27-year period from 1990 to 2017 came to73 people, falling by 150 people from 223 (△67.3%).
The number of fatalities among people age 75 and older over the 27-year period from 1990 to 2017came to 63 people, falling by 58 people from 121 (△47.9%).
Synthesizing the above together reveals that the number of fatalities among people age 16 - 24 havefallen substantially, which has contributed to the drop in the number of fatalities while riding on a
motorcycle. It is also believed that as these people age from this point in time, this will also influence
the change in the number of fatalities among people age 25 - 34, then 35 - 44 and 45 - 54.
People age 16 - 24 were categorized as young people, those age 35 - 54 (including the 35 - 44 and 45- 54 groups) were categorized as middle-aged people, and those 65 and older (including the 65 - 74
and 75+ groups) were categorized as elderly people. Looking at trends in the composition rates foreach of these reveals that in 1990 young people accounted for more than half of the number of fatalities
at 56.8%, yet only 18.2% in 2017. Taking their place were the middle-aged group at 33.7% and elderlygroup at 21.5%, both of which exceeded the share accounted for by young people.
2.3 Changes in the number of fatalities by motorcycle engine displacement (1990 - 2017)
Next, we will look at the trends in the number of fatalities while riding on a motorcycle by engine
displacement. Engine displacement was broadly classified into five categories: 401cc and above, 251- 400cc, 126 - 250cc, 51 - 125cc, and 50cc and below. Table 1 shows the classification of motorcycle
types, while Fig. 3 shows trends in the number of fatalities by engine displacement (1990 - 2017).

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ITARDA 21th WorkShop Report

Table 1. Classification of motorcycle types
Classification on the accident ledger

50cc andbelow

51-125cc

126-250cc

Name in the Road Transport Vehicle Act

Class I
moped

Class II
moped

Light
motorcycle

Requireddriver’s
license251-400cc

401-750cc
Motorcycle

Moped

Can operate

Cannot operate

Ordinary vehicle

Can operate

Cannot operate

Ordinary
motorcycle

Limited tosmall sizes

Can operateNolimitations

751cc andabove

Cannot operate
Can operate

Large motorcycles

Cannot operate
Can operate

Municipality

Yellow /
Peach

White

NumberTransport Bureau

White

Vehicle inspection

Green edging

Not required

RequiredObligation to wear helmet?

Yes

Riding tandem

Not
allowedAllowed (except for cases where the license was obtained lessthan one year ago)

Speed limit

30km/hNo limitations based on vehicle type

National expressways

Cannot enter
50cc andbelow

Can enter

51-125cc

126-250cc

251-400cc

251-400cc

126-250cc

50cc and below

401cc and above

50cc and below

2016

2014

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

401cc and above

401cc and above

Composition rate for eachengine displacement range (%)

Number of fatalities (people)

Classifications in this researchpresentation

51-125cc

Fig. 3. Trends in the number of fatalities by engine displacement (1990 - 2017)

The number of fatalities involving motorcycles with an engine displacement of 401cc and above overthe 27-year period from 1990 to 2017 came to 153 people, increasing by 34 people from 119 (+28.6%).
However, after peaking at 214 people in 2001 this number began to decline, and has remained steadyin recent years.
The number of fatalities involving motorcycles with an engine displacement of 251 - 400cc over the5

ITARDA 21th WorkShop Report27-year period from 1990 to 2017 came to 50 people, falling by 468 people from 518 (△90.3%). This
was the highest rate of decrease seen among all of the engine displacements.
The number of fatalities involving motorcycles with an engine displacement of 126 - 250cc over the
27-year period from 1990 to 2017 came to 112 people, falling by 546 people from 658 (△83.0%).
The number of fatalities involving motorcycles with an engine displacement of 51 - 125cc over the 27year period from 1990 to 2017 came to 133 people, falling by 49 people from 182 (△26.9%). However,this has begun trending upward once again after bottoming out at 103 people in 2013.
The number of fatalities involving motorcycles with an engine displacement of 50cc and below overthe 27-year period from 1990 to 2017 came to 184 people, falling by 831 people from 1,015 (△81.9%).
This accounts for 44.7% of the total decrease for motorcycles as a whole. As such, the decline in thenumber of fatalities while riding on a motorcycle could be claimed to have been largely attributable tothe decline in the number of fatalities involving motorcycles with an engine displacement of 50cc andbelow.
Looking at the changes in the composition rates for each engine displacement reveals that the 50cc andbelow category, which was 40.7% in 1990 and accounted for more than half at 51% in 1999, fell to ashare of 29.1% in 2017. The 401cc and above and 51 - 125cc categories took its place at 24.2% and21.0%, respectively. As this indicates, the 50cc and below category no longer accounts for the majorityof the number of fatalities compared with how things stood before.
2.4 Comparison of past and present characteristics for motorcycle engine displacement and age groups
A comparison of past and present characteristics for each age group and engine displacement was
performed based on the previous section and the section before it. The sum total for the number offatalities over the five-year period from 1990 - 1994 was regarded as past data and compared against
the sum total from the five-year period from 2013 - 2017, which was taken as recent data.
2.4.1.

Characteristics by engine displacement and age group from 1990 - 1994

Fig. 4 shows the number of fatalities by age group and engine displacement (sum total from 1990 1994).

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ITARDA 21th WorkShop Report

Number of fatalities (people)

Composition rate for eachengine displacement range (%)

401cc and above

251-400cc

126-250cc

50cc and below

401cc and above

50cc and below

51-125cc

Fig. 4. Number of fatalities by age group and engine displacement (sum total from 1990 - 1994)

The first characteristic that can be mentioned here is that people age 16 - 24 accounted for a majorityof the whole at 53.4%. As for characteristics of the engine displacement among these, the 126 - 250cc
category accounted for over one-third at 36.2%, followed by 251 - 400cc at 30.5% and 50cc and below
at 24.4%. Motorcycles with an engine displacement of 125 - 250cc, which did not need to undergo
inspections, could drive on national expressways, while those with an engine displacement of 251 400cc had to undergo inspections, but could be driven with a mid-size vehicle license (license
exclusively for mid-sized motorcycles) back then. These and other such reasons are thought to bebehind why they had become increasingly popular among young people (See Table 1).
The composition rate for 401cc and above motorcycles was low on the whole at 20.9% among people
age 25 - 34, 10.5% for those age 35 - 44, and single digits for the other age groups.
As opposed to this, for the composition rate for 50cc and below motorcycles, people age 35 - 44
accounted for more than half at 51.7%, with all age groups age 45 and older accounting for the vast
majority at over 70%.
2.4.2.

Characteristics by engine displacement and age group from 2013 - 2017

Fig. 5 shows the number of fatalities by age group and engine displacement (sum total from 2013 2017). Since the number of fatalities here has decreased substantially compared with that from 1990 1994, the scale of the vertical axis was shrunk by one-tenth (the full scale for Fig. 4 is 10,000 people,
which was reduced to 1,000 people for Fig. 5).

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ITARDA 21th WorkShop Report

Number of fatalities (people)

Composition rate for eachengine displacement range (%)

401cc and above

251-400cc

126-250cc

50cc and below

401cc and above

50cc and below

51-125cc

Fig. 5. Number of fatalities by age group and engine displacement (sum total from 2013 - 2017)

The first thing that can be perceived is the fact that the conspicuously large number of fatalities among
young people (age 16 - 24) that was a characteristic from 1990 - 1994 went away, and the conditions
are such that all age groups are roughly equally represented.
The composition rate for motorcycles with an engine displacement of 50cc and below was 40.7%
among people age 55 - 64, with the vast majority of the age group of people age 65 and older riding
such motorcycles at roughly 70%. Age groups other than those mentioned above (age 54 and younger)
had a comparatively low composition rate at around 20%. The trend for those in the middle-aged andolder groups closely resembled a 23-year shift of the trends from 1990 - 1994 with the passage of time.
The composition rates for motorcycles with an engine displacement of 401cc and above were 31.5%
among people age 25 - 34, 31.2% for those 35 - 44, and 36.0% for those 45 - 54, with each representing
roughly one-third of the total. This is the engine displacement category with the largest number offatalities for these age groups, thus constituting one of the major segments.
2.5. Summary of the changes in and current status of motorcycle accidents
The number of fatalities from motorcycle accidents has continued along its downward trajectory in thesame way as fatalities from the other conditions (while riding in four-wheel vehicles and light vehicles,
while walking, etc.). While the number of fatalities was 2,492 people in 1990, this had fallen to 632 by
2017. This is a large rate of decrease compared with those of the other conditions.
One of the age group-based characteristics is that young people age 16 - 24 once (in the 1990s)
accounted for more than half of the number of fatalities. But as a result of this continuing along its
downward trajectory, recently the middle-aged group (35 - 44 and 45 - 54 age groups) and elderlygroup (65 - 74 and 75 and older age groups) have surpassed young people in terms of their number offatalities.
One of the engine displacement-based characteristics is that the 50cc and below category had continued
on as the condition accounting for nearly half of the number of facilities for a time (1990s - 2000s).

8ITARDA 21th WorkShop Report

But as a result of this continuing along its downward trajectory, recently the gap with the number offatalities from other engine displacement categories, such as 401cc and above, has grown smaller.
Recent trends with the number of fatalities based on engine displacement have exhibited uniquecharacteristics for each age group. For the groups from young adult to middle-aged people (including
the 25 - 34, 35 - 44, and 45 - 54 groups) the 401cc and above category accounted for the greatest
number of fatalities, while for the elderly age group (including the 65 - 74 and 75 and older groups)
the 50cc and below category accounted for the greatest number.
3. Integration with emergency transport data
An attempt was made to perform a new type of analysis by matching the data on emergency transport
times and other topics obtained via the FDMA with the traffic accident data retained by ITARDA andusing the integrated data thus obtained (but only in relation to motorcycles).
3.1. Emergency transport times
Fig. 6 shows a schematic overview of emergency transport times. It offers a schematic representationof the sequence of events that occurs at the scene of the accident after an accident until the victim(s)are admitted to an emergency hospital or similar facility.
Moment contact is madewith the victim

Accident

Scene of theaccident

Arrivalat
scene

Contact

Moment when the victim is finished being
loaded in the ambulance

Loading

Departure
from
scene

Arrival at
hospital

Admission

Emergency
hospitalCallreceived Dispatch
Moment the dispatch
order is issued

Fire department’s
command center

Fig. 6. Emergency transport times

Definitions for the terms found in Fig. 6 are listed below.
・Accident: Moment when the traffic accident occurred・Call received: Moment when the accident report is received (by the fire department’s
command center)

・Dispatch: Moment the order to dispatch an ambulance is issued (by the fire
department’s command center)9

ITARDA 21th WorkShop Report

・Arrival at scene: Moment the ambulance arrives at the scene of the accident

・Contact: Moment the emergency rescue workers made contact with the victim

・Loading: Moment when the victim is loaded in the ambulance

・Departure from scene: Moment when the ambulance departs from the scene of the accident

・Arrival at hospital: Moment the ambulance arrives at the hospital・Admission: Moment the victim is admitted to the hospital

In some cases, terms that are slightly different may be used for each area. The reader is asked to pleasepardon any differences with terms that are in common use.
3.2. Connection between the accident data and emergency transport data
An attempt was made within ITARDA to perform matching between the emergency transport dataobtained via the FDMA with the traffic accident data retained by ITARDA for data related to
motorcycle accidents. Since the emergency transport data obtained covered the two years of 2015 and2016, it was matched with similar data covering two years.
Requirements for performing the matching are defined as follows:• Same prefecture• Same age / gender• Approximately the same occurrence date / time within the traffic accident data and call received
date / time within the emergency transport data
For the requirement of having approximately the same time, efforts were made to improve accuracy
through trial and error.
As a result, the number of valid data points came to approximately 58,000 points. This represents
approximately 40% of the motorcycle accident data points for the year in question.

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Fig. 7 shows an image of the connections between the accident data and emergency transport data.

GenderMotorcycle
type

Route

Age

Prefecture

Type ofarea

Human factor
Travel purpose

Weather

Type ofaccident
Point of personal
harm

Main point ofphysical injury

Danger perception
speedState of main pointof injury

Day ofweek

Emergencytransport time

Day /
night

Extent of physicalinjuries

Personal
protection

Fig. 7. Image of the connections between the accident data and emergency transport data

The blue ovals indicate the major parameters for the traffic accident data retained by ITARDA, while
the blue lines connecting the parameters indicate the connections between the respective parameters.
The connections between respective parameters were derived from the results obtained by performing
analyses on past motorcycle accidents and the like.
The following terms warrant caution:• Personal protection: When riding a motorcycle, this refers to the state of wearing a helmet or
having it come off• Type of area: This refers to the type of land use, including categories such as urban areas withconcentrated populations, other urban areas, and non-urban areas
Estimates regarding how this data on emergency transport times relates to the parameters for this traffic
accident data are expressed via the red oval and red lines. This diagram makes it possible to visuallyperceive how the data on emergency transport times and the parameters for the various accident data
are ultimately related to one another.
Next, predictions for the connection between the data on emergency transport times and accident data
were organized. The predicted connections between the accident data and emergency transport data areshown in Fig. 8.

11ITARDA 21th WorkShop Report

Emergency transport data
Call
Arrival at
Accident received Dispatch scene Contact

Loading

Departurefrom scene

Arrival at Admission
hospital

Motorcycle type
Route

Accident data

Type of area

(1)

Weather

(2)

(3)

(4)

(5)

Weekday
Holiday
Type of accident

(6)
(7)

Travel purpose
Danger perception
speed

Extent of physicalinjuries

(8)
(9)
(10)

Cases where accident data is thought to impact emergency transport time
Cases where emergency transport time is thought to impact accident data

Fig. 8. Predicted connection between the accident data and emergency transport data

The blue arrows express instances where the accident data is believed to affect the emergency transport
data, while the red arrow expresses a case where the emergency transport data is believed to affect theaccident data.
The reasons for why these are assumed to be related are described below.
(1) The accident may be delayed in being discovered depending on the route and type of area at thescene of the accident, which could potentially lead to delays in the time between accident andwhen the call is received, as well as in the time between accident and dispatch (this includes routes
with minimal traffic volume and non-urban areas with minimal traffic volume and pedestrian
traffic, etc.).
(2) Depending on the route and type of area at the scene of the accident (such as in areas deep within
mountains, etc.), if the fire station is located far away from the scene of the accident then this
could potentially lead to delays in the time between dispatch and arrival at scene (time it takes forthe ambulance to head to the scene).
(3) Depending on the route and type of area, if the scene of the accident is located far away from anemergency hospital (such as in areas deep within mountains, etc.), this could potentially lead todelays in the time between departure from scene and arrival at hospital (time it takes for theambulance to head from the scene to the emergency hospital).
(4) Reasons such as poor road conditions on the route taken to travel from the fire station to the sceneof the accident as a result of weather (such as during torrential downpours or when there issnowfall, etc.) can potentially lead to delays in the time between dispatch and arrival at scene(time it takes for the ambulance to head to the scene).
(5) Reasons such as poor road conditions on the route taken to travel from the scene of the accident
to the emergency hospital as a result of weather (such as during torrential downpours or when
there is snowfall, etc.) can potentially lead to delays in the time between departure from scene

12ITARDA 21th WorkShop Reportand arrival at emergency hospital (time it takes for the ambulance to head from the scene to theemergency hospital).
(6) Depending on the day of the week, or if the day is a national holiday, then this could potentiallycause discrepancies with other days regarding the hospital’s admission structure. By limiting theoptions for hospitals to which the patient can be admitted, this ultimately increases the possibilityof delays arising in the time between departure from scene and arrival at hospital.
(7) With single vehicle accidents where the parties have suffered serious injuries and cannot securea means of communication, this may increase the possibility of delays in the time between
accident and when the call is received and the time between accident and dispatch.
(8) When the danger perception speed increases the extent of physical injuries to the parties grows
more severe, a fact that has led to the institution of a policy to shorten response times at the sceneof the accident (called “load and go”). This may shorten the time between arrival at scene and thedeparture from it and other time intervals.
(9) Similar to (8), when the extent of physical injuries is severe, load and go serves as a policy forshortening the response time at the scene of the accident, which may shorten the time between
arrival at scene and the departure from it and other time intervals.
(10) Delays in the time between accident and admission (the total for all of the transport times) may
diminish the possibility that patients in critical condition can receive the help they need.
Based on the above, analyses were performed to see whether there are any connections between theaccident data and the emergency transport data. Fig. 9 shows the connections between the accident data
and the emergency transport data.

Emergency transport data
AccidentCall
received Dispatch

Arrival at
scene

Contact

Loading

Departurefrom scene

Arrival at Admission
hospital

Motorcycle type
Route

Accident data

Type of area
Weather
Weekday
Holiday
Type of accident
Traffic purpose
Danger perception
speed

Extent of physicalinjuries

Acknowledged connection between accident data and emergency
transport times

Fig. 9 Connection between the accident data and emergency transport data

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The number of arrows has increased compared with Fig. 8. This suggests that the accident data andemergency transport data were more closely connected than had been initially anticipated.
Starting from the next section, seven items from a - g in Fig. 9 will be introduced from among theseconnections.

3.3. Characteristics of the time between the accident and dispatch (a, b)
3.3.1. Connection between the time between accident and dispatch and the route (a)Routes were broadly classified into two types: “Expressways” and “general roads.” The term
“expressways” as used here covers both national expressways and motorways. Table 2 shows examplesof national expressways and motorways. In addition, “general roads” refer to roads other thanexpressways as defined above.
Table 2. Examples of national expressways and motorways
Route

RegionRoute name (indicated by their common names)

National
expressways

Hokkaido

Do-o Expressway / Hokkaido Expressway …

TohokuTohoku Expressway / Akita Expressway …

Kanto

Tomei Expressway / Kan-Etsu Expressway

Chubu

Hokuriku Expressway / Chuo Expressway …

Kinki

Meishin Expressway / Chugoku Expressway …

Chugoku

Sanyo Expressway / Okayama Expressway …

Shikoku

Takamatsu Expressway / Matsuyama Expressway …

KyushuKyushu Expressway / Nagasaki Expressway …

Okinawa

Okinawa Expressway

Hokkaido

Hidaka Expressway …

TohokuSendai Tobu Road …

Kanto

Metropolitan Expressway / Ken-O Expressway / Odawara-Atsugi Bypass …

Chubu

Noetsu Expressway / Tokai-Kanjo Expressway / Nagoya Expressway …

Kinki

Hanshin Expressway / Meihan Expressway / Kakogawa Bypass …

Chugoku

Seto-Chuo Expressway / Matsue-Dandan Road …

Shikoku

Matsuyama Soto-Kanjo Road / Ozu Road …

KyushuFukuoka Expressway / Usa-Beppu Road …

Okinawa

Naha Airport Expressway

Motorways

Fig. 10 shows the time between accident and dispatch by route. The horizontal axis shows the time,
expressed as the average value of all of the corresponding data (the same holds true hereafter).

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ITARDA 21th WorkShop Report

Route

Expressway
General road
All

Transport time (minutes)
Accident Call received

Call received Dispatch

Fig. 10. Time between accident and dispatch by route

The first characteristic that can be mentioned is the lengthy time between accident and when the callis received and the time between when the call is received and dispatch on expressways. Whereas thetime between accident and when the call is received is 5.6 minutes on general roads, this is one minute
longer, or 6.6 minutes, on expressways. As for the time between when the call is received and dispatch,while this is 1.8 minutes on general roads it is 0.9 minutes longer, or 2.7 minutes, on expressways. The
results of this indicate that the time between accident and dispatch is 1.9 minutes longer on expressways
as opposed to general roads.
There are a number of conceivable reasons for this, including:(1) Since emergency call phones that are installed at fixed intervals serve as the means of reportingwhen accidents occur along expressways, a considerable time lag may arise.
(2) If people choose the option of stopping their vehicle and reporting the accident from their personal
cell phone, it may take them a certain amount of time to stop their vehicle (along the road shoulder,etc.) while checking to confirm that it is safe to do so since the traffic along expressways moves
at high speeds.

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3.3.2. Connection between the time between accident and dispatch and the accident type (b)Accidents were broadly divided up into four accident types: pedestrian-vehicle, vehicle-vehicle, single
vehicle, and train. Table 3 shows an overview of the categories for each accident type (partiallyomitted).
Table 3. Overview of the categories for each accident type (partially omitted)
Broad category

Intermediate category

Pedestrian-vehicle

While walking facing vehicle

Small category

While walking parallel to vehicle
While crossing the road

Pedestrian crossing / Vicinity of pedestrian crossing …

…
Vehicle-vehicle

Head-on collision
Collision

While passing / Other

Crossing
While passing or overtaking
While passing
While turning left
While turning right

Collision between a vehicle turning right and a vehicle goingstraight on / Other

Other
Single vehicle

Roadside structure

Utility pole / Signpost / Median strip / Central reserve /Median reserve …

Parked vehicle
Running off the road

Fall / Other

Overturn
Other
Train

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ITARDA 21th WorkShop Report

Type of accident

Fig. 11 shows the time between accident and dispatch by type of accident.
Pedestrianvehicle
Vehicle-vehicle
Single vehicle
Train
All

Transport time (minutes)
Accident Call received

Call received Dispatch

Fig. 11. Time between accident and dispatch by type of accident

The first characteristic that can be mentioned is the lengthy time between accident and when the callis received and the time between when the call is received and dispatch for pedestrian-vehicle
accidents. Whereas the time between accident and when the call is received is 5.6 minutes for all
accidents, it is 1.2 minutes longer, or 6.8 minutes, for pedestrian-vehicle accidents. Moreover, while
the time between when the call is received and dispatch is 1.8 minutes for all accidents, it is 1.3 minutes
longer, or 3.1 minutes, for pedestrian-vehicle accidents. The results of this indicate that the time
between accident and dispatch is 2.5 minutes longer for pedestrian-vehicle accidents than it is for all
accidents.
The next thing that can be affirmed from this is the lengthy time between accident and when the call isreceived and the time between when the call is received and dispatch for single vehicle accidents.
Whereas the time between accident and when the call is received is 5.6 minutes for all accidents, it is
0.3 minutes longer, or 5.9 minutes, for single vehicle accidents. As for the time between when the callis received and dispatch, while this is 1.8 minutes for all accidents, it is 0.2 minutes longer, or 2.0
minutes, for pedestrian-vehicle accidents. The results from this indicate that the time between accident
and dispatch takes 0.5 minutes longer for pedestrian-vehicle accidents than it does for all accidents,
which is a minor discrepancy when compared with the time for pedestrian-vehicle accidents.
There are a number of conceivable reasons for this, including:(1) With pedestrian-vehicle accidents, pedestrians tend to suffer more serious injuries thanmotorcyclists do, and there is a strong possibility that the pedestrian will be the secondary party.
Therefore, accident reports for the sake of the pedestrian are prioritized, while those for the
motorcyclist are put off.
(2) With single vehicle accidents, there is the possibility that accident reports will be delayed forreasons such as minimal traffic volume in the surrounding area and the victim being unable tosecure a means of reporting this because they are in critical condition or in shock from theaccident. However, it is not likely that this will lead to substantial delays in the average times.
3.4. Characteristics of the time between dispatch and arrival at scene and the time between departure from17

ITARDA 21th WorkShop Reportscene and arrival at hospital (c, d)
3.4.1.

Connection between the time between dispatch and arrival at scene and the time between
departure from scene and arrival at hospital and the route (c)Similar to the previous section, routes were broadly divided up into expressways and general roads.
Fig. 12 shows the time between dispatch and arrival at scene and the time between departure fromscene and arrival at hospital by route.

Route

Expressway
General road
All

Transport time (minutes)
Dispatch Arrival at scene

Departure from scene Arrival at hospitalFig. 12. Time between dispatch and arrival at scene and time between departure from scene andarrival at hospital by route

The first characteristic that can be mentioned is the lengthy time between dispatch and arrival at scene
and the time between departure from scene and arrival at hospital for expressways. Whereas the time
between dispatch and arrival at scene is 6.3 minutes for general roads, it is 6.2 minutes longer, or nearly
twice as long, on expressways at 12.5 minutes. In addition, while the time between departure fromscene and arrival at hospital is 9.5 minutes for general roads, it is 8.0 minutes longer, or 17.5 minutes,
for expressways. The results of this indicate that the travel time by the ambulance (the total of theabove time intervals) is 14.2 minutes longer on expressways than it is on general roads.
There are a number of conceivable reasons for this, including:(1) When heading to the scene of an accident on an expressway, the ambulance must travel throughan interchange from a general road, which inevitably forces it to travel in a roundabout mannerin many cases.
(2) In addition to (1) above, when the lanes heading in either direction are completely cut off fromone another, the interchanges and so forth that vehicles must pass through are restricted to areasthat are farther up the road, further adding to the possibility that they will have to take aroundabout route.
(3) When congestion occurs on the expressway as a result of the accident occurring, this could
potentially serve as a factor for why it takes more time as it is more difficult to avoid congestion
than it is with general roads.
(4) When heading to the emergency hospital or similar facility from the scene of an accident on an
expressway, just like with (1) the ambulance must pass through an interchange or the like to exit

18

ITARDA 21th WorkShop Report

onto a general road, which inevitably forces it to travel in a roundabout manner in many cases.
(5) In addition to (4) above, when the lanes heading in either direction are completely cut off fromone another, the interchanges and so forth that vehicles must pass through are restricted to areasthat are farther down the road, further adding to the possibility that they will have to take aroundabout route.
Fig. 12 shows a comparison of the time distributions for each transport time designed to further confirm
the status quo, as we only know the difference in the average values. Fig. 13-1 shows the distribution
for the time between dispatch and arrival at scene by route, while Fig. 13-2 shows the distribution for

Composition
rate (%)

the time between departure from scene and arrival at hospital by route.

Time between dispatch - arrival at scene (minutes)
Expressway

General roadFig. 13-1. Distribution for the time between dispatch

Composition
rate (%)

and arrival at scene by route

Time between departure from scene - arrival at hospital (minutes)
Expressway

General roadFig. 13-2. Distribution for the time between departure from scene
and arrival at hospital by route

For both the time between dispatch and arrival at scene and the time between departure from scene andarrival at hospital, expressways have a low composition rate when it comes to short times of fiveminutes or less. This stands in stark contrast with general roads, for which the distribution peaks in thevicinity around five minutes. Conversely, general roads have a composition rate that is close to zero
when it comes to long times for the time between dispatch and arrival at scene of 15 minutes or longer
and the time between departure from scene and arrival at hospital of 23 minutes or longer. As opposedto this, expressways feature a considerable composition rate within these ranges, which can be read asa shift towards longer times on the whole.

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ITARDA 21th WorkShop Report

3.4.2.

Connection between the time between dispatch and arrival at scene and the time between
departure from scene and arrival at hospital and the type of area (d)The type of area can be divided up into three categories: urban areas with concentrated populations,other urban areas, and non-urban areas. Table 4 shows the definitions of terms used for the type of area
categories, while Fig. 14 shows examples of districts with concentrated populations as a supplement
to Table 4.
Table 4. Definitions of terms used for the type of area categories
Broad category

Sub-category

Urban areas

Regions featuring conditions whereby residences, offices, factories, or otherstructures are lined up side by side, or where these are lined up side by side in anintermingled manner, for roughly 500m or more along the side of a road. Suchregions also feature so-called urban area-type configurations in that they consistof at least 80% structures and plots

Non-urban areas

Definition, etc.

Urban areas withconcentrated
populations

Districts with concentrated populations from among
urban areas (according to the national census)

Other urban areas

Areas other than districts with concentrated
populations from among urban areas

Areas other than urban areas

Saitama Prefecture
Hyogo Prefecture

Shizuoka Prefecture

Fig. 14. Examples of districts with concentrated populations

Fig. 15-1 shows the time between dispatch and arrival at scene and the time between departure fromscene and arrival at hospital by type of area.

20

Type of area

ITARDA 21th WorkShop Report

Urban areas withconcentrated population

Other urban areas
Non-urban areas
All

Transport time (minutes)
Accident Arrival at scene

Departure from scene Arrival at hospitalFig. 15-1. Time between dispatch and arrival at scene and time between departure from scene andarrival at hospital by type of area

The first characteristic that can be mentioned is the fact that as you move from urban areas withconcentrated population → other urban areas → non-urban areas, the times between dispatch andarrival at scene and the times between departure from scene and arrival at hospital both grow longer.
If urban areas with concentrated population are taken as the baseline, then the time between dispatch
and arrival at scene is 0.3 minutes longer in other urban areas and 1.9 minutes longer in non-urban
areas. Similarly, the time between departure from scene and arrival at hospital is 1.6 minutes longer inother urban areas and 5.7 minutes longer in non-urban areas.
One reason that could be offered for this is that:(1) The farther you travel into non-urban areas the lower the population density, which in turn isaccompanied by a lower density of the fire stations, emergency hospitals, and other facilities
serving as bases for ambulances and other emergency vehicles. As a result, there is a strong
tendency for the time between dispatch and arrival at scene and the time between departure fromscene and arrival at hospital to be longer.
Furthermore, the ratio between non-urban areas / other urban areas is 1.4-fold for the time between
dispatch and arrival at scene and 1.8-fold for the time between departure from scene and arrival at
hospital, indicating a pronounced tendency regarding the time between departure from scene andarrival at hospital. The trend described in (1) above is more pronounced with emergency hospitals,
which is believed to provide the backdrop for this.
3.5. Characteristics of the time between dispatch and arrival at scene and the time between departure fromscene and arrival at hospital (e)While this is slightly removed from the combination of accident data and emergency transport data,
this section will confirm the connection between the emergency transport times and the extent ofphysical injuries of the injured parties.
Fig. 15-2 shows the time between the accident and admission by the extent of physical injuries.

21

Extent of physical injuries

ITARDA 21th WorkShop Report

Fatality
Serious
injurySlightinjuryAll

Transport time (minutes)
Accident Call received
Contact Loading

Call received Dispatch

Dispatch Arrival at scene

Loading - Departurefrom scene

Departure from scene Arrival at hospital

Arrival at scene Contact
Arrival at hospital Admission

Fig. 15-2. Time between the accident and admission by the extent of physical injuries

The findings that can be read from the figure include the following:(1) With slight injuries, the less injured they are the longer the time between the accident and when
the call is received(2) The shorter the time between dispatch and arrival at scene and the time between departure fromscene and arrival at hospital the slighter the injuries tend to be(3) The shorter the time between contact and loading the slighter the injuries tend to be(4) In fatal cases, the time between loading and departure from scene is short
When these are compared by their average values, the extent of physical injuries is acknowledged as
being related to each respective constituent element for the transport times, but no connection wasrecognized with the total transport time (meaning the time between the accident and admission).
For (4) above, this is thought to be a result that is rooted in “load and go.” As such, the extent ofphysical injuries was investigated for each of the times between contact and departure from the scene,
which is the time from contact, when the extent of the patient’s critical condition can presumably bevisually confirmed, until they depart the scene of the accident.
Fig. 16 shows the distribution for the times between contact and departure from scene and the fatality
rate.

22

Average
value

Fatality rate (%)

Number of casualties(people)ITARDA 21th WorkShop Report

Time between contact and departure from scene (minutes)
Fatality

Serious
injurySlightinjuryFatality rate

Fig. 16. Distribution for the times between contact and departure from scene and the fatality rate

The first characteristic that can be mentioned is that regions with a short time between contact anddeparture from scene have high fatality rates. This is presumed to be an indication of the fact that forpatients in critical condition who ultimately suffer a high fatality rate, the time between contact anddeparture from scene tends to be shorter, which is in accordance with load and go.
The fatality rate for all of the data used is 1.8%. As such, with intersecting points taken as the boundary,
the data was divided up into two cases by whether the time between contact and departure from scene
was 12 minutes or less and 13 minutes or more, and for each of these the fatality rate for each of thetimes between the accident and admission was calculated.
Fig. 17 shows the fatality rate for each time between the accident and admission by the time between
contact and departure from scene.

23

Fatality rate (%)

ITARDA 21th WorkShop Report

Time between accident and admission (minutes)
Fatality rate (time between contact anddeparture from scene: 12 min. or less)

Fatality rate (time between contact anddeparture from scene: 13 min. or more)

Fig. 17. Fatality rate for each time between accident and admission by the time between contact anddeparture from scene

The findings that can be read from the figure include the following:(1) The high fatality rate in regions with short times between the accident and admission involved
cases where the time between contact and departure from scene was 12 minutes or less.
(2) In every case for the times between contact and departure from scene, the longer the time between
the accident and admission the higher the fatality rate tended to be.
The above reveals that load and go is being properly practiced at the scenes of accidents, and thatshortening the emergency transport time lowers the fatality rate.
3.6. Indirect characteristics (f, g)
3.6.1.

Connection between the time between dispatch and arrival at scene and the time between
departure from scene and arrival at hospital by type of motorcycle (f)24

ITARDA 21th WorkShop Report

Motorcycle typeFig. 18 shows the time between dispatch and arrival at scene and the time between departure fromscene and arrival at hospital by type of motorcycle.

All

Transport time (minutes)
Dispatch Arrival at scene

Departure from scene Arrival at hospitalFig. 18. Time between dispatch and arrival at scene and the time between departure from scene andarrival at hospital by type of motorcycle

One characteristic that can be mentioned is that the larger the engine displacement of the motorcycle,
the longer the time between dispatch and arrival at scene and the time between departure from scene
and arrival at hospital.
Taking the overall figure as the baseline, the time between dispatch and arrival at scene was 1.3 minutes
longer for 401 - 750cc motorcycles and 1.9 minutes longer for 751cc and above motorcycles. Similarly,
the time between departure from scene and arrival at hospital was 3.2 minutes longer for 401 - 750cc
motorcycles and 4.6 minutes longer for 751cc and above motorcycles.
The reason for this is that the larger the motorcycle’s engine displacement the longer the time between
dispatch and arrival at scene and the time between departure from scene and arrival at hospital, withthe presumption being that there are many trips taken under these conditions. The non-urban area
category under type of area and expressway category under routes falls under the aforementioned
description.
3.6.2.

Connection between the time between dispatch and arrival at scene / time between departure fromscene and arrival at hospital and the travel purpose (g)The travel purposes were broadly divided up into five categories: Business, commuting to work,commuting to school, touring, etc., and personal. Table 5 shows an overview of the categories for eachtraffic purpose (partially omitted).

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ITARDA 21th WorkShop Report

Table 5. Overview of the categories for each travel purpose (partially omitted)
Broad category

Sub-category

Categories used in 3.6.2

Business

Driving for occupational reasonsBusiness

Commuting to work

Going to / leaving the officeCommuting to work

Commuting to school

Going to school / during class / leaving school

Commuting to school

Personal

Tourism / recreational travel / driving

Touring, etc.

Strolling / dining / shopping / visiting / pick-up / Personal
going to hospital …

Fig. 19 shows the time between dispatch and arrival at scene and the time between departure from

Travel purpose

scene and arrival at hospital by travel purpose.

Business
Commuting to work
Commuting to school
Touring, etc.
Personal
All

Transport time (minutes)
Dispatch Arrival at scene

Departure from scene Arrival at hospitalFig. 19. Time between dispatch and arrival at scene and the time between departure from scene andarrival at hospital by travel purpose

One characteristic that can be mentioned is that both the time between dispatch and arrival at scene
and the time between departure from scene and arrival at hospital are extremely long for touring, etc.
Taking the overall figure as the baseline, the time between dispatch and arrival at scene is 2.0 minutes
longer for touring, etc., while similarly the time between departure from scene and arrival at hospitalis 4.6 minutes longer for this.
The reason for this is presumed to be because in many cases travelers prefer to travel to non-urban
areas for touring, etc.

3.7. Connection with the current status of motorcycle accidents
We will now take a look at the connection between the results mentioned above (3.3 - 3.6) and thecurrent status of motorcycle accidents. Based on the results from 3.6.1, the conditions for accidents forthe 401cc and above engine displacement range that was touched on in Section 2.4 will be analyzed in

26

ITARDA 21th WorkShop Reportterms of the characteristics for motorcycles with large engine displacements.
3.7.1.

Characteristics of the type of area for 401cc and above motorcycles

Fig. 20 shows the number of fatalities by age group and type of area for 401cc or above motorcycles

Average for all
motorcycles: 44.2%

Urban areas withconcentrated populations

Other urban areas

Non-urban areas

Composition rate for
non-urban areas

Composition rate for nonurban areas (%)

Number of fatalities (people)(sum total from 2013 - 2017).

Fig. 20. Number of fatalities by age group and type of area for 401cc or above motorcycles(sum total from 2013 - 2017)

One characteristic that could be mentioned is that non-urban areas account for a high share of thecomposition rate for the number of fatalities for 401cc and above motorcycles. This tendency becomes
more pronounced as you go from young people to the elderly age group. The average value formotorcycles as a whole is 44.2%, whereas for people age 16 - 24 it is approximately 50% and forpeople age 55 and older it is around 80%.
Section 3.4.1 indicated the tendency for the time between dispatch and arrival at scene and the time
between departure from scene and arrival at hospital to be longer in non-urban areas. This suggests thatwith motorcycles that are 401cc and above there is a high probability that their transport times will belonger when there is an accident, which is thought to tie in with the results from section 3.6.1.
3.7.2. Characteristics of the travel purpose for 401cc and above motorcycles
Fig. 21 shows the number of fatalities by age group and travel purpose for 401cc or above motorcycles(sum total from 2013 - 2017).

27

Average for all motorcycles 28%

Business

Commutingto workCommutingto school

Personal

Other

Touring, etc.

Composition rate fortouring, etc. (%)

No. of fatalities (people)

ITARDA 21th WorkShop Report

Touring, etc.

Fig. 21. Number of fatalities by age group and travel purpose for 401cc or above motorcycles(sum total from 2013 - 2017)

One characteristic that could be mentioned is the high composition rate for touring, etc. among thenumber of fatalities for 401cc and above motorcycles. This tendency becomes more pronounced as you
go from young people to the elderly age group. The average value for motorcycles as a whole is 28.0%,
whereas for young people (people age 16 - 24 and 25 - 34) it is over 50% and for people age 55 – 64 it
is higher than 80%.
Section 3.6.2 indicated the tendency for the time between dispatch and arrival at scene and the time
between departure from scene and arrival at hospital to be longer with touring, etc. This suggests thatwith motorcycles that are 401cc and above there is a high probability that their transport times will belonger when there is an accident, which is thought to tie in with the results from section 3.6.1.
3.7.3.

Characteristics of the routes for 401cc and above motorcycles

Fig. 22 shows the composition rates for the number of fatalities for expressways and all routes byengine displacement (sum total from 2013 - 2017).

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ITARDA 21th WorkShop Report

Expressways

All routes

Fig. 22. Composition rates for the number of fatalities for expressways and all routes by engine
displacement (sum total from 2013 - 2017)

The composition rate for motorcycles of 401cc and above accounts for over half of the total number offatalities at 59% on expressways, whereas this is 21% for all routes (expressways + general roads). The
reason for this is believed to be because motorcycles with an engine displacement of 125cc or lesscannot drive on national expressways, which are included among expressways. It is also thought to bebacked by factors like the fact that vehicles with large engine displacements and enormous engine
power output can easily make the most of their advantages on expressways.
Section 3.3.1 indicated the tendency for the time between accident and dispatch to be longer on
expressways, while Section 3.4.1 indicated the tendency for the time between dispatch and arrival atscene and the time between departure from scene and arrival at hospital to be longer on expressways.
This suggests that with motorcycles that are 401cc and above there is a high probability that theirtransport times will be longer when there is an accident, which is thought to tie in with the results fromsection 3.6.1.
3.8. Conclusion from combining the accident data with the emergency transport data
This study affirmed that there are a great many direct and indirect connections between the emergency
transport data and accident data.
A characteristic example found among these is the tendency for the time between accident and dispatch
to be longer on expressways versus general roads. The reason for this is believed to be due to thedifficulty in reporting when accidents occur on expressways.
Similarly, the time between dispatch and arrival at scene and the time between departure from scene
and arrival at hospital tends to be longer on expressways as opposed to general roads. The reason forthis is believed to be because accidents on expressways have a tendency to lead to congestion, which
presumably tends to hinder the travel of ambulances and other emergency vehicles. It is also believed
to be because passing through interchanges and the like carries with it a high possibility of leading to29

ITARDA 21th WorkShop Report

detours.
In addition, it could be mentioned that as opposed to urban areas, non-urban areas tend to have longer
times between dispatch and arrival at scene and times between departure from scene and arrival at
hospital. The reason for this is presumed to be because the fire stations, emergency hospitals, and otherfacilities that serve as bases for ambulances and other emergency vehicles, are sparse compared withurban areas, and tend to be located far apart.
The above represents a direct connection between the emergency transport data and accident data, withindirect connections observed with the type of motorcycle and travel purpose, for which theconnections are striking.
First off, with the type of motorcycle the larger the engine displacement the longer the time between
dispatch and arrival at scene and time between departure from scene and arrival at hospital tended tobe. This is presumed to be backed by the fact that the larger the engine displacement, the greater therate of usage in places like non-urban areas and expressways.
As for the travel purpose, as opposed to business and commuting to work and so forth, touring, etc.
and other such cases where the objective is traveling in itself tend to have longer times between dispatch
and arrival at scene and times between departure from scene and arrival at hospital. The reason for thisis thought to be because with touring, etc. people prefer traveling in non-urban areas, and thus do agreater share of driving there.
With regards to the aforementioned trends with motorcycles with large engine displacements andtouring, etc., when this was compared against recent trends with motorcycle accidents it was found thatthe middle-age group of people driving 401cc and above motorcycles constituted a major segment forthese categories. It was also confirmed that the rate of usage on expressways for the purpose of touring,etc. in non-urban areas was higher than for the other categories. This indicates that the aforementioned
major segment frequently rides their motorcycles under conditions that are unfavorable for emergency
transport.
4. Conclusion and notes
The circumstances surrounding motorcycles have changed significantly compared to the period around1990, with such trends having become particularly manifest among certain age groups and types ofmotorcycles. Around the beginning of the 1990s motorcycles were a young person’s vehicle, with otherage groups mainly preferring mopeds, and when viewed on the whole they were frequently employedfor practical usage purposes. In recent years this has changed such that motorcycles are no longer
necessarily viewed as a young person’s vehicle, with a rising share of people from youths to middleaged people who enjoy riding motorcycles with relatively large engine displacements. As for the
background to this, it is surmised that this trend is partially due to the decline in the population ofyoung people, and their tendency to drift away from riding motorcycles due to the diversification ofyouth-oriented hobbies. It is also partially due to the generation that experienced the motorcycle boomof the 1980s and 1990s continuing to ride motorcycles, or else returning to motorcycles and newly
acquiring motorcycle licenses upon gaining some financial leeway.

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ITARDA 21th WorkShop Report

One recent trend that warrants special mention is the fact that motorcycles with engine displacementsof 401cc and above occupy a large share of the total, with this type of motorcycle accounting for thelargest composition rate among people age 25 - 55. For this domain, the government policy in the pastobligated a need to partially lift the mid-sized restrictions on motorcycle licenses in order to be able todrive a motorcycle with an engine displacement larger than 401cc. The fact that as a result of thechanges to the licensing system in 1996, it became possible to obtain licenses that formerly required
taking an extremely difficult test by ordinary means, is believed to be one of the reasons behind this
(this was changed to ordinary two-wheel licenses: 400cc and below; large- two-wheel licenses:
unrestricted).
The emergency transport data obtained via the FDMA was matched with the traffic accident dataretained by ITARDA, from which it could be ascertained that just under 40% of the total was valid
data. This made it possible to quantitatively perceive phenomena that up until now could only be
discussed qualitatively.
To give one example, there is the extent of the difference in the ambulance travel time (to the scene /to the hospital) depending on the type of area and route, as well as the extent of the difference in thetime from when the accident occurs until the ambulance or other emergency vehicle is dispatcheddepending on factors like the route and type of accident. There is a lack of information on these reasonsand background factors at this point in time, so all that can be done is to conjecture. However, for the
future information must be collected and analyzed in order to reduce the number of fatalities bysupplementing the shortcomings in emergency transport that were quantified above. For this, greater
efforts should be made to request the cooperation of each of the concerned parties.
Moreover, as was described above, for recent major segments a large share of accidents occurs underconditions that are disadvantageous from an emergency transport perspective, which is believed to bebecause a great deal of driving takes place under such situations. It is important that riders bear in mind
the fact that much of their driving is done under such disadvantageous conditions, and make efforts todrive safely and take personal protection into consideration (helmets, clothing, and protective
equipment) on the basis of this.
Moreover, those in administrative positions should be encouraged to carry out system revisions toenable efficient responses when accidents occur, particularly to shorten the delays with ambulances
arriving and transporting patients to hospitals, in order to do everything in their power to do away withsaid disadvantageous conditions for emergency transport.

31