Risk Assessment Data Directory
Report No. 434 – 9
March 2010
Land
transport
accident
statistics
International Association of Oil & Gas Producers
P
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RADD – Land transport accident statistics
contents
1.0
Scope and Application ........................................................... 1
2.0
2.1
2.2
Summary of Recommended Data ............................................ 1
Road and rail users......................................................................................... 1
Dangerous Goods Transport ......................................................................... 4
3.0
3.1
3.2
Guidance on use of data ........................................................ 5
General validity ............................................................................................... 5
Uncertainties ................................................................................................... 5
3.2.1
3.2.2
Road and Rail User Casualty Frequencies .............................................................. 5
DG Transport .............................................................................................................. 5
3.3
Application of frequencies to specific locations ......................................... 5
3.3.1
3.3.2
Road and Rail Transport............................................................................................ 6
Dangerous Goods Transport .................................................................................... 6
4.0
4.1
Review of data sources ......................................................... 7
Basis of data presented ................................................................................. 7
4.1.1
4.1.2
4.1.3
Road Transport........................................................................................................... 7
Rail Transport ............................................................................................................. 8
Dangerous Goods Transport .................................................................................. 10
4.2
Other data sources ....................................................................................... 10
4.2.1
4.2.2
4.2.3
Road Transport......................................................................................................... 10
Rail Transport ........................................................................................................... 11
Dangerous Goods Transport .................................................................................. 11
5.0
Recommended data sources for further information ............ 12
6.0
References .......................................................................... 12
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RADD – Land transport accident statistics
Abbreviations:
ACDS
BLEVE
DfT
DG
DNV
ECMT
E&P
ERA
EU
FEMA
FRA
GB
HGV
IRF
KSI
LGV
LPG
mm
OECD
OG&P
ORR
QRA
RSSB
UIC
UK
US(A)
(V) km
Advisory Committee on Dangerous Substances
Boiling Liquid Expanding Vapour Explosion
Department for Transport
Dangerous Goods
Det Norske Veritas
European Conference of Ministers of Transport
Exploration and Production
European Railway Agency
European Union
Federal Emergency Management Agency
Federal Railroad Administration
Great Britain
Heavy Goods Vehicle
International Road Federation
Killed or Seriously Injured
Light Goods Vehicle
Liquefied Petroleum Gas
millimetre
Organisation for Economic Co-operation and Development
Oil and Gas Producers
Office of Rail Regulation
Quantitative Risk Assessment
Rail Safety and Standards Board
International Union of Railways
United Kingdom
United States (of America)
(Vehicle) kilometre
©OGP
RADD – Land transport accident statistics
1.0
Scope and Application
This datasheet provides information on land transport accident statistics for use in
Quantitative Risk Assessment (QRA). The datasheet includes guidelines for the use of
the recommended data and a review of the sources of the data. Most of the data concern
motor vehicles and rail transport, although some data for cyclists are also presented.
Data excludes pedestrians; if this is needed local data will need to be examined.
The data in this sheet are intended for two main uses:
•
Assessing the risk of transporting personnel; data relating to the frequency of
fatalities and serious injuries to road and rail users are presented.
•
Assessing the risks of transporting Dangerous Goods (DG); data on the frequency of
releases of hazardous materials from rail and road tankers are presented.
In the sections below the following definitions are used:
•
Seriously Injured: Any person not killed, but who sustained an injury as result of an
accident, normally needing medical treatment.
•
Killed: Any person killed immediately or dying within 30 days as a result of an
accident.
•
Road Injury Accident: Any accident involving at least one road vehicle in motion on
a public road or private road to which the public has right of access, resulting in at
least one injured or killed person.
2.0
Summary of Recommended Data
It is best to try and obtain local data where possible. In the absence of local data the
following data can be used.
2.1
Road and rail users
The recommended frequencies and associated data are presented as follows:
•
Road user (Table 2.1, Table 2.2, and Table 2.3)
•
Rail user (Table 2.4)
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RADD – Land transport accident statistics
Table 2.1 Road Accident Fatality and Injury Rates, Selected Countries, All
Vehicles All Rates in deaths or injuries per 10 9 vehicle kilom etres
Country
Year
Traffic
Volume
9
10 vehicle kilometres
Frequency of
Accidents
Resulting in
Injury
9
per 10 vehicle
kilometres
Injury Rate
9
per 10 vehicle
kilometres
Fatality Rate
9
per 10 vehicle
kilometres
Europe
Austria
2004
47.8
892.0
1168.0
18.4
Belgium
2004
93.5
520.5
673.7
12.4
Denmark
2005
45.5
118.9
144.7
7.3
Estonia
2005
8.1
288.1
366.6
20.8
Finland
2005
51.6
136.0
174.0
7.3
France
2005
547.6
154.3
197.2
9.7
Latvia
2005
10.2
439.2
550.7
43.5
Lithuania
2005
8.5
796.1
995.4
90.7
Romania
2004
67.9
101.1
82.4
35.6
Slovenia
2005
11.1
928.4
1289.1
23.2
Sweden
2005
73.8
245.3
358.7
6.0
Switzerland
2005
59.9
362.6
446.9
6.8
Turkey
2005
61.1
8732.2
2520.8
74.0
United Kingdom
2005
493.5
402.7
549.2
6.5
Africa
Egypt, Arab Rep.
2004
28.7
72.5
264.9
46.0
Ghana
2001
15.3
1022.9
472.5*
81.1
Senegal
2000
4.0
1497.9
1114.6*
161.0
South Africa
2005
123.4
1067.9
1597.5
116.0
America
Colombia
2004
15.6
14696.9
351.6
Mexico
2005
91.0
323.9
354.7
51.8
United States
2005
4794.3
386.8
563.0
9.1
Asia/ Middle East
Armenia
2005
0.4
2978.4
4027.2
703.7
Bahrain
2002
5.3
308.9
540.0
15.2
China, HK
2005
10.8
1392.8
1763.3
14.0
Israel
2005
41.1
413.5
863.5
10.9
Japan
2004
781.7
1218.1
10.9
Korea, Rep.
2005
314.9
680.1
1086.8
20.2
Kyrgyz Republic
2005
10.2
365.4
449.3
87.8
Mongolia
2002
2.3
2897.3
2148.8*
178.8
Singapore
2005
13.8
486.6
596.8
12.6
Ukraine
2005
14.0
3319.7
3999.1
516.3
Oceania
New Zealand
2005
40.6
266.1
355.8
9.9
* These appear to be incorrect values as the injury rate should be higher than the injury accident
rate in the previous column.
2
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RADD – Land transport accident statistics
Table 2.2 Recom m ended Road Accident Fatality/Injury Rates:
Rates by Road Class, Road User Type, Injury Severity
All Rates in deaths or injuries per 10 9 vehicle kilom etres
Road User
Pedal Cycle
Motor Cycle
Car
Bus or Coach
LGV
HGV
All Vehicles
Urban roads
Rural Roads
Death
Seriou
s
Injury
Death
Seriou
s
Injury
Death
Motorways
Seriou
s
Injury
Death
All Roads
Seriou
s
Injury
24
65
2
4
11
11
3
490
1220
28
110
6
11
51
58
200
7
3
1
2
8
520
1220
44
29
11
17
52
51
2
41
1
1
2
300
9
11
5
7
10
32
120
4
4
1
1
5
500
1140
31
75
8
12
44
In some circumstances a QRA may require road user casualty rates in different units
which take more account of the specific numbers of passengers being transported.
Thus Table 2.3 presents recommended road user casualty rates per billion passenger
kilometres.
Table 2.3 Recom m ended Road Accident Fatality/Injury Rates:
Rates by Road User Type, Injury Severity All Rates in deaths or injuries per 10 9
passenger kilom etres
Road User
Pedal Cycle
Motor Cycle
Car
Bus or
Coach
LGV/ HGV
Death
36
111
2.7
0.3
KSI*
684
1360
31
11
0.9
11
* KSI = Killed or Seriously Injured
The values in Tables 2.2 and 2.3 are based on UK data and considered representative of
developed countries with good road safety records. The values from Table 2.1 can be
used to generate appropriate modification factors for the rates in Tables 2.2 and 2.3
when applied in different countries. Clearly in any specific situation there will be a
number of factors which will influence accident rates such as driver experience, age,
etc. No data has been found which could represent these influences explicitly.
Table 2.4 Recom m ended Rail Accident Fatality/Injury Rates
All Rates in deaths or injuries per billion passenger kilom etres
Vehicle Type
Rail
1
Death
0.4
Injury
15
See footnote 3 on page 7 for explanation of data derivation
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RADD – Land transport accident statistics
These rail accident data are considered representative of developed countries. In less
developed parts of the world the accident rates may be larger, but no data sources have
been found to enable them to be quantified.
2.2
Dangerous Goods Transport
The data below refers to releases while in transit, not during loading or unloading.
Table 2.5 Recom m ended Rail Tanker Release Frequencies
TANKER
TYPE
TANK SHELL PUNCTURE
(per loaded tank wagon
km)
Motor spirit
LPG
6.3 × 10
-9
2.5 × 10
Ammonia
2.5 × 10
Chlorine
9.0 × 10
EQUIPMENT LEAK
(per loaded tank wagon
hour)
-8
-10
8.3 × 10
-9
1.3 × 10
-9
-10
3.1 × 10
-9
90% of the punctures are taken to be 50 mm diameter holes, the remaining 10%
catastrophic ruptures. The lower chlorine release frequencies are due to higher level of
engineering controls, and possibly safer procedural controls related to handling and
route management. Data on the causal breakdown of the release frequencies is not
available; both internal causes and causes external to the tanker are reflected in the
overall frequencies.
Table 2.6 Recom m ended Flam m able Liquid Road Tanker Release
Frequencies
SPILL SIZE
RELEASE
FREQUENCY
(per loaded vehicle
km)
5 - 15 kg
15 - 150 kg
150 - 1500 kg
> 1500 kg
TOTAL
6.0 × 10
-8
2.6 × 10
-9
7.0 × 10
-8
2.1 × 10
-8
6.0 × 10
-9
Table 2.7 Recom m ended LPG Road Tanker Release Frequencies (not
cylinders)
FAILURE CASE
RELEASE
FREQUENCY
(per loaded vehicle
km)
BLEVE
Cold rupture*
Large* liquid space leak
Large* vapour space leak
-12
2.7 × 10
-9
2.6 × 10
-8
1.8 × 10
-9
2.1 × 10
* Rupture modelled as instantaneous release and large leak modelled as 50 mm diameter hole
4
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RADD – Land transport accident statistics
3.0
Guidance on use of data
3.1
General validity
If transport risk is a relatively small contribution to an overall risk study, the data above
may be sufficient. However, if transport risk is the object of the study, local data
become very important.
As discussed below in Section 3.3, it is strongly recommended that local data sources
on accidents and transport risk are obtained. This is because there can be large local
variations. In recommending the data in Tables 2.5 to 2.7 on DG transport, there is an
implicit assumption that tanker equipment is built to recognised international standards
and operated in line with relevant national DG regulations.
3.2
Uncertainties
3.2.1
Road and Rail User Casualty Frequencies
Due to the relatively large number of road traffic casualties (see Table 4.1 below), the
statistical uncertainties associated with the values in Table 2.2 and Table 2.3 are small
compared to the variations between countries.
In contrast, national statistics for rail passenger fatalities are generally very low.
However, low frequency but high consequence events can have a very large effect on
average passenger risk levels. Thus it is important to consider data over a reasonably
long time period. The data from Table 2.4 are based on British data 1996-2005 which
includes a number of major rail accidents; thus it is considered to be representative
with respect to such events.
Uncertainties for road and rail user casualty rates will be dominated by local variations.
Even within geographically close countries, such as within the EU, variations can be
large (see Section 4.0).
A further source of transport uncertainty arises from use of frequency units (e.g. per
vehicle km or per passenger km). The relative risk of various transport modes can be
highly dependent on the frequency units adopted. Thus, it is recommended that any
conclusions are tested for their sensitivity to units (see Table 2.2 and Table 2.3).
3.2.2
DG Transport
The frequency of releases of hazardous material during transport is much lower than
the frequency of road traffic accidents. Hence the statistical uncertainty will be larger,
similar to typical major hazard QRA uncertainties. In addition, these frequencies will be
influenced by local variations in road and rail accident rates. Thus, local data should be
obtained wherever practicable.
3.3
Application of frequencies to specific locations
This datasheet contains global data plus more detailed national data. When using these
data, it should be realised that they may not be directly applicable to the specific
location under study.
It is therefore strongly recommended that local data sources on accidents and transport
risk from governmental or other national or regional institutions are obtained before
using the data given in this sheet.
Should these local data not be accessible, or their reliability/applicability be uncertain,
then the data in this data sheet could be used after factoring for local circumstances.
©OGP
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RADD – Land transport accident statistics
However, data which have been adjusted to allow for local circumstances should always
be used with caution.
3.3.1
Road and Rail Transport
In assessing the risks of personnel transport the following steps are recommended:
1. Obtain local data if practicable.
2. If not, use the data in Tables 2.1 to 2.4. For road risks the casualty frequencies can
be adjusted for location using the factors suggested in Section 2.0 and presented in
more detail in Section 4.0 below. Some location specific data for rail are also
presented in Section 4.0, but it is unclear if the variations are real or are a feature of
definitions and reporting criteria.
3. Analyse the proposed personnel journey patterns in terms of vehicle types, road
types, vehicle kilometres and/ or passenger kilometres (for rail only passenger
kilometres are required).
4. Multiply the frequencies from steps 1 or 2 with the journey pattern data in step 3 to
obtain overall personnel transport risks. Conduct sensitivity tests using the different
units in Table 2.2 and Table 2.3 (if relevant) and alternative data sources discussed
in section 4.02.
Example: estimate the fatality rate per year for an operation involving 30
personnel being transported 4 times a month by bus/ coach along 300km of
m otorway grade road in North Africa.
Assuming local data specific to this type of operation are not available steps 2 to 4 are
illustrated below.
•
From Table 2.2 for bus/coach the fatality rate is 4 × 10-9 per vehicle-km. This is
based on UK data. From Table 2.1 the overall fatality rates in Egypt are 7.1 times
greater than UK. This is taken as an appropriate multiplication factor. Thus the
fatality rate is 28.4 × 10-9 per vehicle-km.
•
Based on the example information above the number of vehicle-kms per year is 300
× 4 × 12 = 14,400.
•
Thus the annual predicted fatality rate would be 28.4 × 10-9 × 14,400 = 4.1 × 10-4.
Using the data from Table 2.3 which gives a fatality rate per passenger-km gives a
fatality rate per year of 9.2 × 10-4.
3.3.2
Dangerous Goods Transport
In assessing the
recommended:
DG
transport
release
frequencies
the
following
steps
are
1. Obtain local data if practicable.
2. If not, use the data in Tables 2.5 to 2.7 and adjust the release frequencies for location
using fault tree analysis, expert judgements (e.g. based on relative transport
accident rates), or other appropriate methods.
3. Analyse the proposed DG transport patterns in terms of transport mode (rail/ road),
wagon/ vehicle kilometres, loaded tanker hours, etc.
2
While there is uncertainty concerning the location variations in the rail data, as noted above,
the location specific data may be used in sensitivity testing.
6
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RADD – Land transport accident statistics
4. Multiply the frequencies from steps 1 or 2 with the DG transport data in step 3 to
obtain overall release frequencies.
Example: Estimate the frequency per year of large vapour space leaks in an
LPG operation that involves 5 tankers operating each 7 times a week on a
200km route fully loaded.
Assuming local data specific to this type of operation are not available steps 2 to 4 are
illustrated below.
•
From Table 2.7 the large vapour space leak frequency is 2.1 × 10-9 per loaded
vehicle-km. Assume that expert judgement concludes that this frequency is
appropriate.
•
Based on the example information above the number of loaded vehicle-kms per year
is 5 × 7 × 52 × 200 = 364,000.
•
Thus the estimated annual leak frequency is 2.1 × 10-9 × 364,000 = 7.6 × 10-4.
4.0
Review of data sources
4.1
Basis of data presented
4.1.1
Road Transport
Table 2.1 is based on the International Road Federation’s (IRF) 2007 report [10]. For all
countries except Turkey, the most recent year’s data presented in this report is taken as
representative and presented in Table 2.1 (2005 data for Turkey appears to have an error
in the injury rate). This report also provides accident rates per 100,000 head of
population for a wider range of countries. The data in this table can be compared for
trends to the data in the previous Technical Note for E&P Forum which used the IRF’s
1994 report [3].
Table 2.2 and Table 2.3 are based on British data from the Department for Transport’s
2006 report [1]3. Table 4.1 shows the number of fatalities per vehicle type for 2006 on
which the casualty rates are based.
Table 4.1 GB Num bers of Fatalities 2006: Num bers by Road User Type &
Severity
Road User
Pedal Cycle
Motor Cycle
Car
Bus or Coach
LGV
HGV
All vehicles
Death
153
634
2580
122
280
419
3172
KSI*
2568
6992
26713
1260
2322
2119
31845
* KSI = Killed or Seriously Injured
[1] also provides a much greater range of data including trends over time, accident rates
as a function of age, gender, alcohol levels etc.
One of the E&P Forum (as was) member companies collected statistical data in the
1990s from which accident rates for desert driving conditions can be calculated. This
3
In Table 2.1 in 2006 there were no fatalities on urban roads for LGVs and HGVs and no fatalities
on motorways for bus/ coach. For these cells of the table, the recommended fatality rates have
been set to the “All Roads” value. In Table 2.2 the rates are based on 1996-2005 data; as no
separate value for HGV is given in Ref. [1] it has been set at the LGV value.
©OGP
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RADD – Land transport accident statistics
data covers a period between 1992 and 1994. The derived desert driving accident and
fatality rates are shown in Table 4.2 below and relate to company and contractor work
related accidents.
Table 4.2 Desert Driving Accident and Fatality Rates
Year
Road Traffic
(108 V km)
Road Traffic
Accidents
Injuries
Fatalities
1992
0.79
137
56
4
Fatality Rate
(per 108 V km)
5.1
1993
0.89
135
42
2
2.3
1994
0.86
111
26
0
0.0
The downward trend in the fatality rate was considered to be the result of improved
induction training, the fitting of roll-over bars and speed governors to all LGVs and the
near 100% usage of seat-belts. This needs to be taken into account when applying the
rates for desert driving at other locations. Deriving an average over the 3 years of 2.4
fatalities per 108 vehicle kilometres, this is approximately 5 times higher than the
average all-vehicle GB fatality rate.
4.1.2
Rail Transport
Table 2.4 is based on British data from 1996 to 2005 [1].
In analysing rail casualty data, care needs to be taken to distinguish casualties caused
in train incidents, non-train incidents and vandalism/ suicide. Overall fatality numbers
are dominated by the latter category. In addition, statistics may include passengers,
staff and “others” (third parties who were neither passengers nor staff, but who were
killed or injured due to rail related activity).
Also there is the need to allow for low frequency but high consequence events which
are characteristic of rail operations. A national railway may experience several years of
very few fatalities and then have one event which kills many tens of people.
It is often difficult to determine what has been included in summary statistics. Table 2.4
above is a subset of DfT data comparing various transport modes. It is averaged over
10 years and therefore takes account of low frequency/ high consequence events (e.g.
Ladbroke Grove, where there were 31 fatalities). The casualty rates relate just to train
passengers, but from all accident causes not only train accidents such as collisions,
derailments, fires etc.
Further details of UK rail accident rates are provided in the UK Office of Rail Regulation
Annual reports [4]. These split out incidents involving passengers, staff and members of
the public, and provide train incident rates, as well as other accident categories such as
trespass and vandalism.
The GB data is considered representative of average EU data. Figure 4.1 below is taken
from the RSSB strategic plan [5] and compares UK passenger fatality rates against the
25 EU countries’ averages. The UK values are shown to be consistent with the EU
values except in years when there are major UK disasters. If the major disasters were to
be averaged over a few years, there would be an even closer match.
In recent years the European Railway Agency has begun to collect statistics from all the
European countries. The 2004-2005 Rail Statistics are summarised in Figure 4.2 below
[6]. These data would appear to indicate significant differences between EU countries.
However, there is a need to be cautious. The variation could be because of inconsistent
reporting criteria or it could reflect low frequency/ high consequence events affecting a
8
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RADD – Land transport accident statistics
few countries in the time period 2004-2005. Given this uncertainty no potential
modification factors are suggested in this datasheet.
Figure 4.1 Com parison between GB and EU Average Rail Fatality Rate [5]
Figure 4.2 EU States Rail Fatality Rate [6]
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RADD – Land transport accident statistics
US data from the Federal Railroad Administration [7] for 2006 indicates 2 passenger
fatalities in 16,211,393,401 passenger miles = 0.08 fatalities per billion passenger km.
This is also consistent with UK data for 2004-2005.
4.1.3
Dangerous Goods Transport
Tables 2.5 to 2.7 present a selection of available data suitable for use only where
transport risks form a small contribution to a process QRA. They should not be used for
transport QRA without detailed consideration of the applicability of the data. In
particular local variations in transport accident rates should be analysed.
4.1.3.1 Rail Tankers
The Advisory Committee on Dangerous Substances (ACDS) of the UK Health & Safety
Commission produced a report in 1991 [8] which provides a detailed QRA of road and
rail transport of motor spirit, LPG, ammonia and chlorine in Great Britain, including
puncture frequencies based on modified UK experience and equipment leak frequencies
based on fault tree analysis.
[8] estimated frequencies of tank shell punctures and equipment leaks from tank
wagons carrying dangerous goods, based on modified UK data (Table 2.5). The
punctures are taken to be 50 mm diameter holes (90%) or catastrophic ruptures (10%).
4.1.3.2 Liquid Tankers
The best available estimate of leak frequencies from tankers carrying non-pressurised
liquids is also given by [8], based on spills from UK motor spirit tankers (Table 2.6).
4.1.3.3 LPG Road Tanker Leak Frequencies
A DNV Technica report [9] compared various sources of leak frequency data for LPG
road tankers, and developed a fault tree model to take account of the main influences.
Table 2.7 gives the failure case frequencies for a tanker with passive fire protection,
based on Hong Kong road traffic accident rates.
4.2
Other data sources
4.2.1
Road Transport
The International Road Federation in Geneva collects world road statistics including
data on road accidents from a large number of countries [10]. The data include the
annual number of accidents, annual number of injured and killed people as well as the
number of injury accidents, persons injured or killed per 100 million vehicle kilometres
(108 V km).
The Organisation for Economic Co-operation and Development (OECD) maintains road
safety statistics [2]. It presents international fatality information for different road types.
The OECD website [2] also presents injury rates and fatalities per 100,000 of the
population.
The European Conference of Ministers of Transport [11] gives death rates and casualty rates per capita
and per vehicle for European countries and Australia, Canada, Japan, Russia and USA. However, it does
not have any estimates of vehicle-km.
Davies & Lees [12] give a variety of accident statistics for heavy goods vehicles, drawn
mainly from national accident statistics.
10
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RADD – Land transport accident statistics
Koornstra [24] presents a passenger transport model which includes road transport
risk. Reference risks are first determined based on data from the original 15 EU
countries. Multiplication factors are then developed relating road fatality risks to the
Gross National Income per person (GNI/p) and plotted on a graph with a fitted function.
Corrections are made for estimated underreporting. The report notes a rather wide
scatter of fatality rates for individual countries about the curve. For certain countries
there is a difference between the predicted and reliably established risks (where country
specific data exists). Thus the report proposes an additional multiplication factor where
there are strong indications that a country is relatively less safe or relatively safer than
other countries with a comparable GNI/p level. Finally a multiplication factor for road
type proportions is proposed based on the variation in risk that is seen on different road
types. In principle this method can estimate road transport risks for any country in the
world and could be useful when country specific data is not available. The reference
risks are consistent with those presented in this report.
4.2.2
Rail Transport
A Statistical Analysis of Fatal Collisions and Derailments of Passenger Trains on British
Railways [13] provides a detailed analysis of the comparative safety of different designs
of passenger carriage on British Railways, including accidents per passenger mile and
fatalities per accident.
Frequency of Railway Accidents in the German Federal Railways Network: Goods Traffic and
Shunting Operations [14] provides a detailed analysis of accident frequencies and
involvement probabilities for wagons in goods trains in Germany.
Light Rail Accidents in Europe and North America [15] has a detailed comparison of
accident frequencies on light rail systems in different countries.
The report by Koornstra [24] also includes rail transport risk. Reference risks are
determined based on data from the original 15 EU countries. Multiplication factors are
again developed relating rail fatality risks to the Gross National Income per person
(GNI/p). However there is less country data than for road fatalities on which to base
these multiplication factors.
Thus, as with road, the report proposes using an
additional multiplication factor where there are strong indications that a country is
relatively less safe or relatively safer than other countries with a comparable GNI/p
level.
Further international information on rail transport safety is available from International
Union of Railways (UIC) at http://www.uic.asso.fr/.
4.2.3
Dangerous Goods Transport
There are a large number of other data sources with information relevant to DG
transport, but generally they are older or less generally applicable than the values given
in Section 2.0.
The Federal Emergency Management Agency (FEMA) [16] provides information for
explosive, flammable and otherwise dangerous chemicals. It presents failure rates
which originate from several sources. The age of the background data and the
individual sources may no longer reflect the reliability of transport vehicles on the roads
and railways today because of stricter safety regulations for both vehicles and materials
transportation. The individual sources contain information about accident rates for
trucks used in the petroleum industry and for transporting bulk hazardous materials
([17] to [23]).
©OGP
11
RADD – Land transport accident statistics
5.0
Recommended data sources for further information
For further information, the data sources used to develop the release frequencies
presented in Section 2.0 and discussed in Sections 3.0 and 4.0 should be consulted.
The references used for the recommended data in Section 2.0 are shown in bold in
Section 6.0.
6.0
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
12
References
Departm ent for Transport 2006. Road Casualties Great Britain 2006
http://www.dft.gov.uk/162259/162469/221412/221549/227755/rcgb2006v1.pdf
OECD, International Traffic Safety Data and Analysis Group
http://cemt.org/IRTAD/IRTADPublic/we2.html
International Road Federation (IRF) 1994. World Road Statistics 1980-1993
Office of Rail Regulation (ORR) 2006. Annual Report on Railway Safety
2005. http://www.rail-reg.gov.uk/upload/pdf/296.pdf
UK Rail Safety and Standards Board (RSSB) 2007. The Railway Strategic Safety Plan
2008-2010.
European Railway Agency (ERA) 2006. A Summary of 2004-2005 EU Statistics on
Railway Safety.
http://www.era.europa.eu/public/Documents/Safety/Safety_Performance/0705%20ERA-Report2.pdf
US Federal Railroad Administration website:
http://safetydata.fra.dot.gov/OfficeofSafety/
ACDS 1991. M ajor Hazard Aspects of the Transport of Dangerous
Substances, Advisory Com m ittee on Dangerous Substances, Health &
Safety Com m ission, HMSO.
DNV Technica 1996. Quantitative Risk Assessment of the Transport of
LPG and Naphtha in Hong Kong - Methodology Report, Report for
Electrical & Mechanical Services Departm ent, Hong Kong Governm ent,
Project C6124.
International Road Federation 2007. The IRF W orld Road Statistics
2007, Data 2000-2005.
ECMT 1998. Statistical Report on Road Accidents 1993/1994, European Conference of
Ministers of Transport, OECD, Paris.
Davies, P.A. & Lees, F.P. 1992. The Assessment of Major Hazards: The Road
Transport Environment for Conveyance of Hazardous Materials in Great Britain, J.
Haz. Mat., 32, 41-79.
Evans, A.W. 1997. A Statistical Analysis of Fatal Collisions and Derailments of
Passenger Trains on British Railways: 1967-1996, Proc. Inst. Mech. Eng., 211 Part F.
Fett, H-J & Lange, F 1992. Frequency of Railway Accidents in the German Federal
Railways.
Walmsley, D.A. 1992. Light Rail Accidents in Europe and North America, Research
Report 335, Transport & Road Research Laboratory, Crowthorne, UK
Federal Emergency Management Agency. Handbook of Chemical Hazard Analysis
Procedures, available from Federal Emergency Management Agency, Publications
Office, 500 C Street, SW, Washington, DC 20472
American Petroleum Institute 1983. Summary of Motor Vehicle Accidents in the
Petroleum Industry for 1982.
Dennis, A.W. et al. 1978 Severities of Transportation Accidents Involving Large
Packages, Sandia Laboratories, NTIS SAND-77-0001.
Rhoads, R.E. et al. 1978 An Assessment of the Risk of Transporting Gasoline by Truck,
prepared by Pacific Northwest Laboratory for the U.S. Department of Energy, PNL2133.
©OGP
RADD – Land transport accident statistics
[20] Smith, R.N. and E.L. Wilmot 1982. Truck Accident and Fatality Rates Calculated from
California Highway Accident Statistics for 1980 and 1981, prepared by Sandia National
Laboratories for the U.S. Department of Energy, SAND-82-7066.
[21] National Safety Council. 1988 Accident Facts.
[22] Ichniowski T. 1984 New Measures to Bolster Safety in Transportation, Chemical
Engineering, pp. 35-39.
[23] Urbanek, G.L. and E.J. Barber 1980. Development of Criteria to Designate Routes for
Transporting Hazardous Materials, prepared by Peat, Marwick, Mitchell and Co. for
the Federal Highway Administration, NTIS PB81-164725.
[24] Koornstra, M.J. 2008. A Model for the Determination of the Safest Mode of Passenger
Transport between Locations in any Region of the World. Report for Shell International
Exploration and Production B.V.
©OGP
13
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