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Research Report
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
Ahmad Noor Syukri Zainal Abidin Siti Atiqah Mohd FaudziFauziana LaminAbdul Rahmat Abdul Manap
MRR 05/2012
Research Report
MIROS Crash Investigation and Reconstruction Annual Statistical Report 2007–2010
Ahmad Noor Syukri Zainal AbidinSiti Atiqah Mohd FaudziFauziana LaminAbdul Rahmat Abdul Manap
MIROS © 2012 All Rights Reserved
Published by:
Malaysian Institute of Road Safety Research (MIROS)Lot 125-135, Jalan TKS 1, Taman Kajang Sentral,43000 Kajang, Selangor Darul Ehsan.
For citation purposes
Ahmad Noor Syukri ZA, Siti Atiqah MF, Fauziana L & Abdul Rahmat AM (2012), MIROS Crash Investigation and Reconstruction Annual Statistical Report 2007–2011, MRR 05/2012, Kuala Lumpur: Malaysian Institute of Road Safety Research.
Printed by: MIROS
Font type: Myriad Pro LightSize: 11 pt / 15 pt
DISCLAIMERNone of the materials provided in this report may be used, reproduced or transmitted, in any form or by any means, electronic or mechanical, including recording or the use of any information storage and retrieval system, without written permission from MIROS. Any conclusion and opinions in this report may be subject to reevaluation in the event of any forthcoming additional information or investigation.
Perpustakaan Negara Malaysia Cataloguing-in-Publication Data
Research report. MIROS crash investigation and reconstruction : annual statistical 2007-2010 / Ahmad Noor Syukri Zainal Abidin ... [et al.] Research report : MRR 05/2012Bibliography: p. 61ISBN 978-967-5967-27-61. Traffic safety--Malaysia. 2. Roads--Safety measures--Malaysia. 3. Traffic regulations--Malaysia. I. Ahmad Noor Syukri Zainal Abidin.363.1252109595
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Contents
List of Figures vList of Tables viiDefinitions ixAcknowledgements xiiiPreface xv
1.0 Introduction 1
2.0 Descriptive Analyses 3 2.1 Investigated Cases 3 2.2 Investigated Cases by Fatalities 4 2.3 Investigated Cases by Day of Occurrence 4 2.4 Investigated Cases by Time of Occurrence 6 2.5 Investigated Cases by Month of Occurrence 8 2.6 Investigated Cases by State 10 2.7 Investigated Cases by District 12 2.8 Investigated Cases by Crash Type 16 2.9 Investigated Cases by Vehicle Type 18 2.10 Investigated Cases by Number of Vehicles Involved 19 2.11 Investigated Cases by Road Type 21 2.12 Investigated Cases by Intersection Type 23 2.13 Investigated Cases by Horizontal Profile of the Road 25 2.14 Investigated Cases by Vertical Profile of the Road 25 2.15 Investigated Cases by Carriageway Type 26 2.16 Investigated Cases by Vicinity Area 27 2.17 Investigated Cases by Weather Condition 28 2.18 Investigated Cases by Lighting Condition 29
3.0 KSI and Fatality Index 30 3.1 Fatality and KSI Indexes by Day of Occurrence 31 3.2 Fatality and KSI Indexes by Time of Occurrence 32 3.3 Fatality and KSI Indexes by Month of Occurrence 32 3.4 Fatality and KSI Indexes by State 33
Page
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3.5 Fatality and KSI Indexes by Crash Type 35 3.6 Fatality and KSI Indexes by Road Type 36 3.7 Fatality and KSI Indexes by Intersection Type 36 3.8 Fatality and KSI Indexes by Horizontal Profile of the Road 37 3.9 Fatality and KSI Indexes by Vertical Profile of the Road 37 3.10 Fatality and KSI Indexes by Carriageway Type 38 3.11 Fatality and KSI Indexes by Number of Vehicles Involved 38 3.12 Fatality Index by Vehicle Type 39 3.13 Fatality and KSI Indexes by Vicinity Area, Weather and 39 Lighting Conditions
4.0 Injury and Crash Occurrence Factors 41 4.1 Fatalities 41 4.2 Month of Occurrence 42 4.3 Time of Occurrence 44 4.4 Crash Type 45 4.5 Vehicle Type 47 4.6 Number of Vehicles Involved 48 4.7 Road Type 49 4.8 Intersection Type 50 4.9 Horizontal Profile of the Road 51 4.10 Vertical Profile of the Road 52 4.11 Carriageway Type 53 4.12 Vicinity Area 54 4.13 Weather Condition 56 4.14 Lighting Condition 57
5.0 Conclusion 59
References 61
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List of Figures
Figure 1 Distribution of investigated cases, 2007–2010 3Figure 2 Investigated cases by fatalities per case, 2007–2010 4Figure 3 Investigated cases by day of occurrence, 2007 5Figure 4 Investigated cases by day of occurrence, 2008 5Figure 5 Investigated cases by day of occurrence, 2009 5Figure 6 Investigated cases by day of occurrence, 2010 6Figure 7 Investigated cases by time of occurrence, 2007 6Figure 8 Investigated cases by time of occurrence, 2008 7Figure 9 Investigated cases by time of occurrence, 2009 7Figure 10 Investigated cases by time of occurrence, 2010 7Figure 11 Investigated cases by month of occurrence, 2007 8Figure 12 Investigated cases by month of occurrence, 2008 9Figure 13 Investigated cases by month of occurrence, 2009 9Figure 14 Investigated cases by month of occurrence, 2010 9Figure 15 Investigated cases by state, 2007 10Figure 16 Investigated cases by state, 2008 10Figure 17 Investigated cases by state, 2009 11Figure 18 Investigated cases by state, 2010 11Figure 19 Investigated cases by crash type, 2007 16 Figure 20 Investigated cases by crash type, 2008 16 Figure 21 Investigated cases by crash type, 2009 17 Figure 22 Investigated cases by crash type, 2010 17 Figure 23 Investigated cases by vehicle type, 2007 18 Figure 24 Investigated cases by vehicle type, 2008 18 Figure 25 Investigated cases by vehicle type, 2009 19 Figure 26 Investigated cases by vehicle type, 2010 19 Figure 27 Investigated cases by number of vehicles involved, 2007 20Figure 28 Investigated cases by number of vehicles involved, 2008 20 Figure 29 Investigated cases by number of vehicles involved, 2009 20 Figure 30 Investigated cases by number of vehicles involved, 2010 21 Figure 31 Investigated cases by road type, 2007 21 Figure 32 Investigated cases by road type, 2008 22 Figure 33 Investigated cases by road type, 2009 22
Page
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Figure 34 Investigated cases by road type, 2010 23Figure 35 Investigated cases by intersection type, 2007 23 Figure 36 Investigated cases by intersection type, 2008 24 Figure 37 Investigated cases by intersection type, 2009 24 Figure 38 Investigated cases by intersection type, 2010 24 Figure 39 Investigated cases by horizontal profile of the road, 2007–2010 25Figure 40 Investigated cases by vertical profile of the road, 2007–2010 26Figure 41 Investigated cases by carriageway type, 2007–2010 26 Figure 42 Investigated cases by vicinity areas, 2007 27 Figure 43 Investigated cases by vicinity areas, 2008 27 Figure 44 Investigated cases by vicinity areas, 2009 28 Figure 45 Investigated cases by vicinity areas, 2010 28 Figure 46 Investigated cases by weather condition, 2007–2010 29 Figure 47 Investigated cases by lighting condition, 2007–2010 29 Figure 48 Number of causalities by injury severity 30
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List of Tables
Table 1 Investigated cases by district, 2007 12Table 2 Investigated cases by district, 2008 13 Table 3 Investigated cases by district, 2009 14 Table 4 Investigated cases by district, 2010 15Table 5 Fatality and KSI indexes by day of occurrence 31 Table 6 Fatality and KSI indexes by time of occurrence 32Table 7 Fatality and KSI indexes by month 33 Table 8 Fatality and KSI indexes by state 34Table 9 Fatality and KSI indexes by crash type 35Table 10 Fatality and KSI indexes by road type 36 Table 11 Fatality and KSI indexes by intersection type 37Table 12 Fatality and KSI indexes by horizontal profile of the road 37 Table 13 Fatality and KSI indexes by vertical profile of the road 38Table 14 Fatality and KSI indexes by carriageway type 38Table 15 Fatality and KSI indexes by number of vehicles involved 39Table 16 Fatality index by vehicle type 39 Table 17 Fatality and KSI indexes by vicinity area 40 Table 18 Fatality and KSI indexes by weather condition 40 Table 19 Fatality and KSI indexes by lighting condition 41 Table 20 Number of fatalities per case by injury and crash occurrence factors 42 Table 21 Distribution of injury and crash occurrence factors by month of occurrence 43 Table 22 Distribution of injury and crash occurrence factors by time of occurrence 44 Table 23 Injury and crash occurrence factors by crash type 46Table 24 Injury and crash occurrence factors by vehicle type 47Table 25 Injury and crash occurrence factors by number of vehicles involved 48 Table 26 Injury and crash occurrence factors by road type 49 Table 27 Injury and crash occurrence factors by intersection type 50 Table 28 Injury and crash occurrence factors by horizontal profile of the road 51 Table 29 Injury and crash occurrence factors by vertical profile of the road 53
Page
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Table 30 Injury and crash occurrence factors by carriageway type 54 Table 31 Injury and crash occurrence factors by vicinity area 55 Table 32 Injury and crash occurrence factors by weather condition 56 Table 33 Injury and crash occurrence factors by lighting condition 57
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Definitions
Carriageway Any information related to the existence of road median at the crash site, and is categorised as single carriageway for roads without medians, and dual carriageway for roads with median
Casualty Any person killed or injured as a result of the crash
Crash Type Any information related to crash configuration, and is categorised into head-on collision, rear collision, side collision, rollover collision, and hitting object collision
Environment Any information related to weather, lighting and area in the vicinity of crash
Horizontal Profile Any information related to the horizontal design of the road, and is categorised into straight and curve
Intersection Any information related to the road geometrical design, and is categorised into midblock, crossroad, staggered junction, T-junction, and Y junction
Lighting Any information related to the source of light or natural illumination, and is categorised into daylight, dark with lighting, dark without lighting, and dawn or dusk
Location Regional information of the crash, and is categorised into state and district
Road Any public road and any other road to which the public have access and includes bridges, tunnels, lay-by, ferry facilities, interchanges, traffic islands, road dividers, traffic lanes, acceleration/deceleration lanes, exit ramps, toll plazas, service areas and other structures and fixtures to fully effect its use (Road Transport (Amendment) Act 2010)
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Road Type Road type is categorised into municipal, expressway, federal, private, and state:
Municipal roads are the roads which are under the territory of municipal council/city hall (Royal Malaysian Police, Pol27)
Expressways are defined as divided roads for through traffic with full control of access and always with grade separations at all intersections (A Guide on Geometric Design of Road, REAM 1997)
Federal roads are the designated federal territory road and roads declared to be federal under federal law (Road Transport (Amendment) Act 2010)
State roads are the designated state territory road and roads declared to be under state government authority
Private roads are roads which are maintained and kept by private person or private bodies
Temporal The temporal information of crash, and is categorised into day, time and month
Vehicle A structure capable of moving or being moved or used for the conveyance of any person or thing on which maintains contact with the ground when in motion (Road Transport (Amendment) Act 2010)
Number of Vehicle Information related to the number of vehicle involved in a crash, and is categorised into single, two-vehicle and multiple vehicle
Vertical Profile Any information related to the vertical design of the road and is categorised into flat for road stretch without gradient inclination/declination and slope for road stretch with gradient inclination/declination
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Vehicle Type All types of vehicle and is categorised into passenger vehicles, buses, trucks/trailers or motorcycles. Passenger vehicles include cars, vans, sports utility vehicles (SUV), multi-purpose vehicles (MPV), four-wheel drives and pickup trucks
Vicinity Prominent natural or man-made structure in the surrounding area at the crash site and is categorised into wood area, school, agricultural, residential, construction, industrial, bridge and others
Weather Meteorological information of the condition during the time of crash and is categorised into fine, rainy, drizzling or foggy
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Acknowledgements
We would like to express our deep appreciation to the Director-General of Malaysian Institute of Road Safety Research (MIROS), Professor Dr. Wong Shaw Voon, and the acting Director of Vehicle Safety and Biomechanics Research Centre, Ir. Fuad bin Abas for extending full support in producing this report. Our deep gratitude also goes out to all Research Officers, Assistant Research Officer and Research Assistants from the Crash Reconstruction Unit for conducting and facilitating the data sorting and transferring process during the case profiling activities. Our appreciation also goes for all Crash team members who contributed to the data collection process during crash investigation operation, which the data was utilised in this report. Last but not least, our special thanks to our partners; especially to the Traffic Department of Royal Malaysian Police (RMP) and Road Safety Department for providing assistance during the crash investigations.
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Preface
The publication of MIROS Crash Investigation and Reconstruction Annual Statistical Report is the first issue of the statistical presentation of in-depth crash investigation data. This report contains the analysis of crash data investigated by MIROS from 2007 to 2010. The main aim is to provide more comprehensive representation and interpretation of crash investigation data from the attended crashes.
This report contains six sections. Section 1 provides an overview of MIROS as the organisation that conducts the in-depth crash investigation, the methods and approaches of the investigation process, and the potential interventions deduced from the findings. Section 2 provides the definition of the terminologies used in the report. Sections 3 to 5 present the summary of crash data analysis in graphical illustration and detailed tables and include descriptive analysis, analysis of ‘Killed and Severely Injured’ (KSI), fatality index and crash occurrence and injury factors. Section 6 highlights the conclusion.
It is hoped that this report provides information and reference to related agencies involved in the automotive, transportation planning and safety sectors to benefit the Malaysian road safety planning and development. MIROS gratefully acknowledges the cooperation of all parties and personnel, particularly the Royal Malaysian Police (RMP) Traffic Division in assisting the data collection process. All comments and suggestions for future improvement of the report are greatly welcomed and appreciated.
PROFESOR DR. AHMAD FARHAN BIN MOHD SADULLAHFormer Director-GeneralMalaysian Institute of Road Safety Research (MIROS), July 2011
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1.0 Introduction
MIROS conducts numerous research projects to cater for road safety issues in Malaysia. In order to recommend high impact interventions towards road safety, MIROS not only concentrates on research projects but also conducts on-field operations. One of the essential cores of MIROS’ operation is the real-world in-depth crash investigation. This continuous effort started in March 2007, almost as early as the establishment of MIROS on 3 January 2007.
Pillared by three research centres that cover three main aspects of road safety—roads, vehicles and human issues—MIROS’ crash investigation operation is under the responsibility of the Vehicle Safety and Biomechanics Research Centre (VSB). Under the centre, the management of the operation is organised by a unit known as the Crash Reconstruction Unit (CRU). The primary purpose of MIROS’ crash investigation is to identify in detail as many factors as possible that contribute to crashes and the resulting injuries to occupants, particularly factors that have not been previously identified. This process is expected to lead to the development of countermeasures that will help to reduce the human and economic impact of road crashes on Malaysian society.
MIROS’ crash investigation work covers all types of road traffic collisions in Malaysia including Sabah and Sarawak. Crash investigation is conducted by a team of eight core members, nine associate members and several supporting members. The current strength of the team is to cover three cases at a time. A team of two or three crash analysts is dispatched to a crash site to collect physical data and evidence such as crash configuration data, crash vehicles, the environment, the road profile, and injury details with the help of Traffic Investigation Officer (IO) of the Royal Malaysian Police (RMP). The team then uses the
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data and evidence to reconstruct the accident and suggests recommendations for improvement. From March 2007 until December 2010, MIROS has analysed 439 road traffic collisions.
However, MIROS’ crash investigation team only attends cases that meet specific requirements. The team only attends to:
• crashes that involve any type of vehicles with three fatalities or above;
• crashes that involve commercial vehicles with one fatality or above;
• crashes with many fatalities, and trigger the ministry’s inquiry and national interest;
• crashes or cases related to the current or future research by MIROS; and
• cases of special requests from other government and external agencies.
Findings from MIROS’ crash investigations not only highlight future potential research, but are also used as indicators for high impact interventions and baselines for new national policies towards road safety.
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2.0 Descriptive Analyses
Section 2 will describe the distribution of cases according to five parameters, which are investigated cases, temporal dimension, crash types, vehicle information, and road information. The temporal dimension of the crashes is further classified into day, time and month of occurrence. The crash type is further classified into vehicle types and number of vehicles involved. The vehicle information is further classified into types of roads and types of carriageway. Road information is further classified into the horizontal and vertical profiles of the road and road geometry.
2.1 Investigated Cases
From 2007 through 2010, a total number of 439 cases were investigated by MIROS’ crash investigation team. The distribution of the investigated cases in each year is presented in Figure 1. The highest number of investigated cases is in 2008 displays with 170 cases, followed by years 2009 and 2010. The lowest number of investigated cases is in 2007 as MIROS’ crash investigation operation only started in March of the said year.
Investigated Crashes
Num
ber o
f cas
es
180160140120100806040200
2007 2008 2009 2010
Figure 1 Distribution of investigated cases, 2007–2010
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2.2 Investigated Cases by Fatalities
Cases involving one to three fatalities show the highest proportion throughout the four-year data (Figure 2). This proportion is also contributed by the specific requirements for investigation that limit crashes involving passenger cars with three fatalities or above and crashes involving commercial vehicles with at least one fatality. Crashes with no fatality show the lowest frequencies across all four years.
Figure 2 Investigated cases by fatalities per case, 2007–2010
Fatalities
Num
ber o
f cas
es
2.3 Investigated Cases by Day of Occurrence
No consistent pattern is observed according to the cases’ day of occurrence. The investigated cases show a scattered distribution between each day of occurrence and the weekend showed no significant effect to crash frequencies compared to weekdays (Figure 3–6).
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Figure 3 Investigated cases by day of occurrence, 2007
Num
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f cas
es
Day
Figure 4 Investigated cases by day of occurrence, 2008
Num
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es
Day
Num
ber o
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es
Day
Monday
Tuesd
ay
Wednesday
Thursday
Friday
Saturday
Sunday
Figure 5 Investigated cases by day of occurrence, 2009
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2.4 Investigated Cases by Time of Occurrence
Figures 7 through 10 show the distribution of the investigated cases by time of occurrence. The number of investigated cases occurring during wee hours (12:00 a.m. to 5:59 a.m.) is noticeably high in three of the four years. However, the pattern differs in 2009 (Figure 9) when crashes that occurred during morning hours (mainly the time when people travel to work) comprise the highest proportion. For other categories of time period, no prominent pattern is observed.
Num
ber o
f cas
es
Day
Monday
Tuesd
ay
Wednesday
Thursday
Friday
Saturday
Sunday
Figure 6 Investigated cases by day of occurrence, 2010
Num
ber o
f cas
es
Time
Figure 7 Investigated cases by time of occurrence, 2007
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Num
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f cas
es
Time
Figure 8 Investigated cases by time of occurrence, 2008
Num
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es
Time
Figure 9 Investigated cases by time of occurrence, 2009
Num
ber o
f cas
es
Time
Figure 10 Investigated cases by time of occurrence, 2010
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2.5 Investigated Cases by Month of Occurrence
The distribution of investigated cases is higher during the third to the early fourth quarter (July to October) of 2009 and 2010, as presented in Figures 13 and 14. However, in 2008, the year with the highest number of investigated cases, high frequency of cases accumulate around the second quarter, specifically between March and June (Figure 12). The lower distribution of the investigated cases in early to mid-2007 is due to the fact that those were the early days of MIROS’ crash investigation team formation, which started to operate in March 2007 and came to full force in the ending phase of the year.
Figure 11 Investigated cases by month of occurrence, 2007
Num
ber o
f cas
es
Month
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Num
ber o
f cas
es
Month
Figure 12 Investigated cases by month of occurrence, 2008
Num
ber o
f cas
es
Month
Figure 13 Investigated cases by month of occurrence, 2009
Num
ber o
f cas
es
Month
Figure 14 Investigated cases by month of occurrence, 2010
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2.6 Investigated Cases by State
Looking across the data by states, Perak consistently shows a high distribution of investigated cases for all four years. The number of investigated cases in Pahang is the highest for three of the four years (refer to Figures 15, 17 and 18). Meanwhile, Johor and Selangor display similar distributions and can be considered as high rated states in terms of the number of investigated cases.
Num
ber o
f cas
es
State
Figure 15 Investigated cases by state, 2007
Num
ber o
f cas
es
State
Figure 16 Investigated cases by state, 2008
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Num
ber o
f cas
es
State
Figure 17 Investigated cases by state, 2009
Num
ber o
f cas
es
State
Figure 18 Investigated cases by state, 2010
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2.7 Investigated Cases by District
Tables 1 through 4 show the distribution of investigated cases from 2007 through 2010 in all involved districts, which also represent District Police Headquarters.
Note: The district with the highest frequency is boxed in red
Table 1 Investigated cases by district, 2007
District Frequency District Frequency
Baling 1 Muar 2
Bandar Pemaisuri 1 Paloh Hinai 1
Batu Pahat 1 Pekan 1
Bentong 1 Raub 1
BP Cenderawaseh 1 Seberang Perai Selat 1
BP Gambang 1 Sepang 2
Butterworth 1 Seremban 1
Gombak 1 Seremban 2 2
Gerik 4 Seri Alam 1
Gua Musang 3 Setiu 1
Ipoh 2 Slim River 1
Jitra 1 Taiping 1
Johor Bahru (Selatan) 1 Tapah 1
Johor Bahru (Utara) 1 Tawau 1
Jalan Bandar 6 Temerloh 1
Keningau 2 Timur Laut 2
Klang 2 TOTAL 61
Kota Setar 3
Kuala Kangsar 1
Kuala Kubu Bharu 1
Kuala Selangor 1
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Table 2 Investigated cases by district, 2008
Note: The district with the highest frequency is boxed in red
District Frequency District Frequency
Balik Pulau 1 Kunak 1
Barat Daya 1 Muadzam 2
Beluran 1 Muar 14
Bentong 1 Pasir Putih 3
Cameron Highlands 1 Pekan 2
Gombak 4 Petaling Jaya 3
Gerik 3 Putrajaya 2
Gua Musang 3 Rembau 4
Hulu Selangor 2 Rompin 2
Ipoh 4 Seberang Jaya 1
Jalan Bandar 8 Seberang Perai Tengah 2
Jasin 1 Segamat 1
Jitra 1 Semporna 1
Johor Bahru Selatan 1 Sepang 3
Johor Tebrau 1 Seremban 5
Kajang 4 Seri Alam 3
Kampar 3 Serian 2
Kangar 1 Setiu 2
Kemaman 2 Shah Alam 2
Kerian 1 Slim River 2
Klang 2 Subang Jaya 3
Kluang 1 Taiping 1
Kota Belud 2 Tampin 1
Kota Kinabalu 1 Tanjung Malim 3
Kota Setar 3 Tapah 6
Kota Tinggi 3 Teluk Intan 1
Krian 1 Timur Laut 1
Kuala Kangsar 1 Ungku Aminah 1
Kuala Krai 1 Yan 1
Kuala Kubu Baru 2 Machang 1
Kuala Lipis 2 Manjung 2
Kuala Muda 5 Maran 1
Kuala Selangor 6 Marang 1
Kuala Terengganu 1 Mersing 1
Kuantan 3 Miri 1
Kubang Pasu 1 TOTAL 175
Kulai Jaya 5
Kulim 1
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Table 3 Investigated cases by district, 2009
Note: The district with the highest frequency is boxed in red
District Frequency District Frequency
Alor Gajah 1 Port Dickson 2
Batu Pahat 3 Putrajaya 1
Beaufort 1 Rembau 1
Bentong/Mentakab 4 Sandakan 1
Besut 1 Seberang Perai Utara 1
Dungun 2 Selayang 1
Gerik 3 Seremban 2
Gombak 3 Serian 1
Gua Musang 3 Shah Alam 1
Hilir Perak 1 Sungai Besar 1
Hulu Selangor 2 Taiping 1
Ipoh 2 Tanah Merah 1
Jalan Bandar 5 Tapah 1
Jelebu 1 Temerloh 3
Kampar 2 Timur Laut 1
Kerian 1 Machang 1
Kluang 1 Maran 4
Kota Bharu 1 Meradong 1
Kota Setar 1 Mersing 1
Kota Tinggi 2 Miri 2
Kuala Krai 1 Padang Besar 1
Kuala Langat 2 Pasir Puteh 1
Kuala Lipis 1 Pekan 1
Kuala Muda 2 Penampang 1
Kuala Pilah 1 Petaling Jaya 2
Kuala Selangor 1 Ledang 1
Kuantan 7 TOTAL 100
Kulai Jaya 3
Kulim 1
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Table 4 Investigated cases by district, 2010
Note: The district with the highest frequency is boxed in red
District Frequency District Frequency
Alor Gajah 1 Port Dickson 2
Bandar Baharu 1 Raub 2
Banting 1 Rembau 2
Batu Pahat 2 Rompin 4
Beluran 1 Seberang Perai Tengah 1
Bentong 1 Seberang Perai Utara 2
Besut 1 Segamat 2
Betong 1 Seremban 3
Gerik 2 Seri Alam 1
Gombak 1 Setiu 1
Gua Musang 2 Sik 1
Hilir Perak 1 Sri Aman 1
Hulu Selangor 3 Taiping 1
Ipoh 3 Tampin 1
Jalan Bandar 7 Tanah Merah 1
Jasin 1 Tanjung Malim 1
Jelebu 1 Tawau 2
Jempol 2 Timur Laut 1
Kajang 1 Kulim 1
Kampar 2 Lahad Datu 4
Klang 3 Maran 2
Kluang 1 Marang 2
Kota Kinabalu 1 Mersing 1
Kota Samarahan 1 Muar 2
Kota Tinggi 1 Mukah 1
Kuala Kangsar 2 Pasir Mas 1
Kuala Kubu Baru 1 Pasir Puteh 1
Kuala Lipis 1 Pekan 2
Kuala Pilah 1 Petaling Jaya 1
Kuantan 1 TOTAL 97
Kubang Pasu 2
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2.8 Investigated Cases by Crash Type
In terms of crash type, hitting object and head-on collisions are the two most frequent crash types. In 2007, 13 cases of hitting object collisions were investigated, which contribute to the highest percentage of crash type for that particular year (Figure 19). This is followed by head-on collision, which recorded nine cases. In 2008, both types of crashes show similar distribution of pattern ranging from 43 to 45 cases (Figure 20).
Figure 19 Investigated cases by crash type, 2007
Num
ber o
f cas
es
Crash type
Num
ber o
f cas
es
Crash type
Figure 20 Investigated cases by crash type, 2008
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Referring to Figures 21 and 22, for 2009 and 2010, head-on collision is the most common type of crash, with 32 and 30 cases investigated, respectively. Hitting object collision turns out to be the second highest type of crash, with 20 cases investigated in 2009 and 2010.
Num
ber o
f cas
es
Crash type
Figure 21 Investigated cases by crash type, 2009
Num
ber o
f cas
es
Crash type
Figure 22 Investigated cases by crash type, 2010
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2.9 Investigated Cases by Vehicle Type
Passenger cars, which include vans, multi-purpose vehicles (MPV), sports utility vehicles (SUV) and four-wheel drives (4WD), are the most common types of vehicles involved in the overall investigated cases for 2007 through 2010 (Figures 23 through 26). Lorries and buses are the next most common types of vehicles in the investigated cases. Meanwhile, motorcycles are recorded among the lowest vehicle type involved in the investigated cases throughout the four-year period.
Num
ber o
f veh
icle
s
Vehicle type
Figure 23 Investigated cases by vehicle type, 2007
Num
ber o
f veh
icle
s
Vehicle type
Figure 24 Investigated cases by vehicle type, 2008
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Num
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f veh
icle
s
Vehicle type
Figure 25 Investigated cases by vehicle type, 2009
Figure 26 Investigated cases by vehicle type, 2010
Num
ber o
f veh
icle
s
Vehicle type
2.10 Investigated Cases by Number of Vehicles Involved
For all four years, the highest proportion of the investigated cases involves crashes between two vehicles. As shown in Figures 27 through 30, two-vehicle crashes comprise approximately 50% of the total number of investigated cases each year. Single-vehicle crashes also show a significant proportion of crash frequencies. However, in 2009, the number of investigated multiple-vehicle crashes shows a slight increment and possesses similar distribution with crashes involving single vehicles.
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Num
ber o
f cas
es
Vehicle involved
Figure 27 Investigated cases by number of vehicles involved, 2007
Figure 28 Investigated cases by number of vehicles involved, 2008
Num
ber o
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es
Vehicle involved
Num
ber o
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es
Vehicle involved
Figure 29 Investigated cases by number of vehicles involved, 2009
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2.11 Investigated Cases by Road Type
In 2007, the highest number of investigated cases occurred on federal roads (Figure 31), which contributes to 45% of the total number of investigated cases for the year. The same pattern is observed in 2010 with crashes on federal roads consisting of 51% of overall investigated cases (Figure 34).
Figure 30 Investigated cases by number of vehicles involved, 2010
Num
ber o
f cas
es
Vehicle involved
Figure 31 Investigated cases by road type, 2007
Num
ber o
f cas
es
Road type
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In 2008, crashes on expressways and federal roads show similar proportion, with approximately 60 cases being investigated in each type of roads (Figure 32). On the other hand, 2009 data show that more than 40% of the investigated cases occurred on state roads, and this is followed by those occurred on expressways (32%) (Figure 33).
Figure 33 Investigated cases by road type, 2009
Num
ber o
f cas
es
Road type
Num
ber o
f cas
es
Road type
Figure 32 Investigated cases by road type, 2008
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2.12 Investigated Cases by Intersection Type
A huge majority of all investigated cases from 2007 through 2010 occurred at midblock stretches as shown in Figures 35 through 38. The proportion of crashes occurring at midblock is prominently significant throughout the four-year period with an average percentage of 85% per year. Investigated cases at junctions show a considerably equal distribution according to the different types of intersection designs.
Num
ber o
f cas
es
Road type
Figure 34 Investigated cases by road type, 2010
Figure 35 Investigated cases by intersection type, 2007
Intersection
Num
ber o
f cas
es
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Intersection
Num
ber o
f cas
es
Figure 36 Investigated cases by intersection type, 2008
Figure 38 Investigated cases by intersection type, 2010
Intersection
Num
ber o
f cas
es
Intersection
Num
ber o
f cas
es
Figure 37 Investigated cases by intersection type, 2009
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2.13 Investigated Cases by Horizontal Profile of the Road
In terms of the horizontal profile of roads, there are consistently higher investigated cases at straight stretches compared to curves, and this observed pattern is consistent for the four-year period. In 2008, the number of investigated cases occurring at straight stretches is 108 cases from the total number of 178 cases investigated for the year (Figure 39).
Figure 39 Investigated cases by horizontal profile of the road, 2007–2010
Horizontal profile
Num
ber o
f cas
es
2.14 Investigated Cases by Vertical Profile of the Road
The overall distribution of the cases is illustrated in Figure 40. There are higher number of investigated cases on flat roads. The pattern is consistent for all the years but is plotted highest in 2008 (67.4%).
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2.15 Investigated Cases by Carriageway Type
No consistent pattern was observed in terms of the investigated cases according to carriageway type. The data show higher number of investigated cases at dual carriageway roads compared to single carriageway for three years except in 2008, when the total number of investigated cases is the highest (Figure 41).
Figure 40 Investigated cases by vertical profile of the road, 2007–2010
Vertical profile
Num
ber o
f cas
es
Figure 41 Investigated cases by carriageway type, 2007–2010
Intersection
Num
ber o
f cas
es
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0 2 4 6 8 10 12 14 16 18 20
Agricultural
1o34truc5o3
Mix
Shoplot
2007
2.16 Investigated Cases by Vicinity Area
Throughout the four-year period, crashes that occurred within the vicinity of wooded area are the most prominently investigated (Figures 42–45). Other areas have a more scattered and lower distribution in terms of the number of cases although crashes at agricultural and residential areas record a slightly higher number of investigated cases.
Figure 43 Investigated cases by vicinity areas, 2008
Figure 42 Investigated cases by vicinity areas, 2007
Vici
nity
Number of cases
0 10 20 30 40 50 60 70 80 90
AgriculturalBridge
8onstruc<onIndustrial
Mix@esiden<al
SchoolShoplot
Wood Area
2008
Vici
nity
Number of cases
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2.17 Investigated Cases by Weather Condition
The majority of the investigated cases occurred during fine weather (Figure 46). The proportion of investigated cases during fine weather for 2008 is over presented, with more than 70%, and is significantly higher than those that occurred in any other weather condition, especially in 2009 and 2010.
Figure 44 Investigated cases by vicinity areas, 2009
Vici
nity
Number of cases
Figure 45 Investigated cases by vicinity areas, 2010
Vici
nity
Number of cases
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2.18 Investigated Cases by Lighting Condition
The data in terms of lighting condition show that for the total number of investigated cases from 2007 through 2010, crashes that occurred during daylight (6:30 a.m. until 6:30 p.m.), when it is safe to say that visibility is not a major concern, show the highest frequency (Figure 47). However, crashes during dark condition and without lighting, which are related to the said issue, are also significant and come in second place in all four years in terms of the number of investigated cases.
Weather
Num
ber o
f cas
es
Figure 46 Investigated cases by weather condition, 2007–2010
Figure 47 Investigated cases by lighting condition, 2007–2010
Lighting
Num
ber o
f cas
es
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3.0 KSI and Fatality Index
The 439 investigated cases during the four-year period (2007 to 2010) recorded 2,395 casualties. From these casualties, 47% (1,131 persons) were fatally injured, 31% (735 persons) sustained severe injuries, while the remaining 22% (529 persons) were slightly injured (Figure 48).
Figure 48 Number of causalities by injury severity
Injury severity
Num
ber o
f per
son
Based on the number of casualties, the indexes for fatality and killed and severely injured (KSI) are calculated to measure the severity of the crash according to selected parameters. The KSI index is calculated based on the number of fatal and seriously injured person. Slightly injured and non-injured person are not considered in the calculation. The KSI index calculation is shown in the equation below:
KSI Index = (No. of Fatalities + No. of Serious Injuries) / No. of Cases Equation 1
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A study by Nursitihazlin (2006) mentioned that according to Radin Umar (2003), the fatality index is the number of deaths per road accident. It is used to show the level of seriousness of accidents’ death rate in a time period. Fatality index calculation is shown below:
Fatality Index = No. of Fatalities / No. of Cases Equation 2
The KSI and fatality indexes per case are calculated and discussed according to different parameters in the following sections of the report.
3.1 Fatality and KSI Indexes by Day of Occurrence
Table 5 illustrates the distribution of KSI and fatality indexes according to day of crash occurrence. Based on the data, Tuesday records the highest KSI, with 4.94 per case, while Sunday records the highest fatality, with 2.93 fatalities per case.
Parameters Number of cases
Casualties Number of occupants
Index
Monday 67 Fatal 189 2.82
KSI 296 4.48
Tuesday 64 Fatal 155 2.42
KSI 316 4.94
Wednesday 50 Fatal 114 2.28
KSI 176 3.52
Thursday 55 Fatal 125 2.27
KSI 195 3.55
Friday 49 Fatal 123 2.51
KSI 222 4.53
Saturday 72 Fatal 193 2.68
KSI 293 4.07
Sunday 75 Fatal 220 2.93
KSI 350 4.67
Table 5 Fatality and KSI indexes by day of occurrence
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3.2 Fatality and KSI Indexes by Time of Occurrence
Table 6 shows distribution of KSI and fatality indexes according to time of crash occurence. In terms of time of occurrence, 9:01 a.m.–12:00 p.m. and 4:01 p.m.–8:00 p.m. are the peak periods, with 3.89 and 7.91 fatalities and killed and severely injured per case recorded respectively.
3.3 Fatality and KSI Indexes by Month of Occurrence
Fatality index is highest in October, with 3.14 fatalities per case from 2007 through 2010, while KSI index is highest in March, with 5.56 killed and severely injured per case (Table 7).
Table 6 Fatality and KSI indexes by time of occurrence
Parameters Number of cases
Casualties Number of occupants
Index
0:01 a.m.–6:00 a.m. 97 Fatal 268 2.89
KSI 427 5.73
6:01 a.m.–9:00 a.m. 54 Fatal 119 1.19
KSI 163 1.49
9:01 a.m.–12:00 p.m. 54 Fatal 157 3.89
KSI 242 5.64
12:01 p.m.–2:00 p.m. 39 Fatal 102 1.58
KSI 200 6.69
2:00 p.m.–4:00 p.m. 38 Fatal 94 1.88
KSI 147 3.69
4:01 p.m.–8:00 p.m. 60 Fatal 151 2.06
KSI 346 7.91
8:01 p.m.–12:00 a.m. 55 Fatal 151 1.35
KSI 220 2.13
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Table 7 Fatality and KSI indexes by month
Parameters Number of cases
Casualties Number of occupants
Index
January 31 Fatal 76 2.45
KSI 144 4.65
February 28 Fatal 57 2.04
KSI 76 2.71
March 34 Fatal 97 2.85
KSI 189 5.56
April 31 Fatal 93 3.00
KSI 153 5.10
May 30 Fatal 68 2.27
KSI 96 3.20
June 33 Fatal 82 2.48
KSI 140 4.24
July 35 Fatal 100 2.86
KSI 157 4.49
August 39 Fatal 101 2.59
KSI 148 3.79
September 39 Fatal 89 2.28
KSI 194 4.97
October 50 Fatal 157 3.14
KSI 210 4.20
November 39 Fatal 106 2.72
KSI 166 4.26
December 43 Fatal 93 2.16
KSI 175 4.07
3.4 Fatality and KSI Indexes by State
Table 8 shows the distribution of KSI and fatality indexes according to states in Malaysia. From the table, Malacca records the highest KSI index of 9.60 and fatality index of 4.00 although it has one of the lowest number of high profile cases.
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Table 8 Fatality and KSI indexes by state
Parameters Number of cases
Casualties Number of occupants
Index
Johor 60 Fatal 163 2.72
KSI 271 4.52
Kedah 26 Fatal 68 2.62
KSI 102 3.92
Kelantan 29 Fatal 89 3.07
KSI 116 4.00
Kuala Lumpur 27 Fatal 41 1.52
KSI 86 3.19
Malacca 5 Fatal 20 4.00
KSI 48 9.60
Negeri Sembilan 31 Fatal 72 2.32
KSI 101 3.26
Pahang 57 Fatal 159 2.79
KSI 228 4.00
Perak 65 Fatal 199 3.06
KSI 400 6.15
Perlis 3 Fatal 7 2.33
KSI 11 3.67
Penang 18 Fatal 28 1.56
KSI 43 2.39
Putrajaya 3 Fatal 5 1.67
KSI 15 5.00
Sabah 20 Fatal 70 3.50
KSI 109 5.45
Sarawak 11 Fatal 35 3.18
KSI 60 5.45
Selangor 61 Fatal 121 1.98
KSI 198 3.30
Terengganu 16 Fatal 42 2.63
KSI 60 3.75
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3.5 Fatality and KSI Indexes by Crash Type
Table 9 shows that rollover crashes have the highest KSI index of 6.06 among the crash types but the lowest fatality of 1.33. Head-on crashes have the highest fatality index of 3.06 compared to other types of crashes. The result shows that although fatality is highest in head-on crashes, rollover crashes are the highest cause for killed or severely injured occupants.
Table 9 Fatality and KSI indexes by crash type
Parameters Number of cases
Casualties Number of occupants
Index
Head-on 115 Fatal 352 3.06
KSI 485 4.22
Hitting animal 1 Fatal 3 3.00
KSI 3 3.00
Hitting object 97 Fatal 251 2.59
KSI 450 4.69
Hitting pedestrian
9 Fatal 19 2.11
KSI 25 2.78
Multiple event 42 Fatal 126 3.00
KSI 241 5.74
Rear impact 58 Fatal 123 2.12
KSI 239 4.12
Rollover 18 Fatal 24 1.33
KSI 109 6.06
Side impact 51 Fatal 134 2.63
KSI 174 3.41
Side swept 7 Fatal 14 2.00
KSI 20 2.86
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3.6 Fatality and KSI Indexes by Road Type
The distribution of fatality and KSI indexes according to type of road is shown in Table 10. Crashes on expressways record the highest KSI index of 5.11, while crashes on private roads show the highest fatality index of 3.00. The results show that an average, five occupants were killed or seriously injured in a crash along an expressway for the investigated cases.
Table 10 Fatality and KSI indexes by road type
Parameters Number of cases
Casualties Number of occupants
Index
Municipal 1 Fatal 2 2.00
KSI 2 2.00
Expressway 130 Fatal 318 2.45
KSI 664 5.11
Federal 169 Fatal 462 2.73
KSI 644 3.81
Private road 1 Fatal 3 3.00
KSI 5 5.00
State 127 Fatal 320 2.52
KSI 512 4.03
3.7 Fatality and KSI Indexes by Intersection Type
In terms of intersection type, fatality index is highest at crashes that occurred on crossroads with 2.71 fatalities per case, while KSI index is highest at crashes happening at Y-junctions, with 5.00 KSI per case.
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Table 11 Fatality and KSI indexes by intersection type
Parameters Number of cases
Casualties Number of occupants
Index
Crossroad 7 Fatal 19 2.71
KSI 29 4.14
Midblock 332 Fatal 876 2.64
KSI 1493 4.50
Staggered junction
6 Fatal 14 2.33
KSI 17 2.83
T-junction 27 Fatal 69 2.56
KSI 85 3.15
Y-junction 10 Fatal 13 1.30
KSI 50 5.00
Table 12 Fatality and KSI indexes by horizontal profile of the road
Parameters Number of cases
Casualties Number of occupants
Index
Curve 145 Fatal 403 2.78
KSI 705 4.90
Straight 252 Fatal 628 2.49
KSI 1025 4.07
3.8 Fatality and KSI Indexes by Horizontal Profile of the Road
Table 12 displays the KSI and fatality indexes according to the horizontal profile of roads, with curved roads showing the highest KSI and fatality indexes per case of 4.90 and 2.78, respectively.
3.9 Fatality and KSI Indexes by Vertical Profile of the Road
Table 13 shows that sloping roads show the highest KSI and fatality indexes of 5.25 and 3.20, respectively.
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Table 14 Fatality and KSI indexes by carriageway type
3.10 Fatality and KSI Indexes by Carriageway Type
Table 14 shows that dual carriageway roads have the highest KSI index of 4.53, while fatality index is highest at single carriageway roads with 2.67 fatalities per case. However, only marginal difference of 0.11 was found between the two types of carriageway.
Parameters Number of cases
Casualties Number of occupants
Index
Dual 183 Fatal 469 2.56
KSI 825 4.53
Single 212 Fatal 567 2.67
KSI 910 4.29
3.11 Fatality and KSI Indexes by Number of Vehicles Involved
Although the numbers of single-vehicle accidents are not as frequent compared to two-vehicle crashes, KSI and fatality indexes for single-vehicle crashes are the highest with 4.94 KSI and 2.78 fatalities per accident (Table 15).
Table 13 Fatality and KSI indexes by vertical profile of the road
Parameters Number of cases
Casualties Number of occupants
Index
Flat 265 Fatal 632 2.38
KSI 1075 4.06
Slope 117 Fatal 374 3.20
KSI 609 5.25
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Table 15 Fatality and KSI indexes by number of vehicles involved
Parameters Number of cases
Casualties Number of occupants
Index
Single-vehicle 140 Fatal 389 2.78
KSI 691 4.94
Two vehicles 229 Fatal 586 2.56
KSI 899 3.93
Multiple vehicles
61 Fatal 139 2.28
KSI 255 4.18
Parameters Total number of occupants
Number of fatal occupants
Index
Passenger vehicle 1381 763 0.55
Lorry 285 69 0.24
Bus 1924 146 0.08
Motorcycle 72 45 0.63
Table 16 Fatality index by vehicle type
3.12 Fatality Index by Vehicle Type
As shown in Table 16, motorcycles, which are classified as one of the vulnerable road users (VRU), record the highest fatality index (0.63) compared to other types of vehicles. Meanwhile, heavy vehicles, such as buses and lorries with higher crash compatibility, possess among the lowest fatality index with 0.08 fatality per crash.
3.13 Fatality and KSI Indexes by Vicinity Area, Weather and Lighting Conditions
Tables 17, 18, and 19 report the KSI and fatality indexes according to the environmental components of the crashes, namely the vicinity area, weather conditions and lighting conditions.
In terms of the environmental components of the crashes, fatality index is recorded highest for crashes happening at agricultural areas (2.86), during drizzling condition (4.84) and when the
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Table 18 Fatality and KSI indexes by weather condition
Parameters Number of cases
Casualties Number of occupants
Index
Drizzling 23 Fatal 89 4.84
KSI 158 7.39
Fine 296 Fatal 757 2.23
KSI 1213 4.70
Foggy 4 Fatal 6 1.73
KSI 11 2.21
Raining 59 Fatal 148 1.79
KSI 308 7.56
Table 17 Fatality and KSI indexes by vicinity area
Parameters Number of cases
Casualties Number of occupants
Index
Agricultural 58 Fatal 166 2.86
KSI 230 3.97
Bridge 11 Fatal 29 2.64
KSI 43 3.91
Construction 11 Fatal 23 2.09
KSI 41 3.73
Industrial 14 Fatal 26 1.86
KSI 40 2.86
Mix 17 Fatal 32 1.88
KSI 55 3.24
Residential 61 Fatal 164 2.69
KSI 210 3.44
School 4 Fatal 4 1.00
KSI 6 1.50
surrounding is dark without any lighting (2.67). Meanwhile, KSI index is highest for crashes that occurred at agricultural areas (3.97), during rainy day (7.56), and during dawn or dusk (7.44).
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4.0 Injury and Crash Occurrence Factors
In this section, factors related to injury and crash occurrence are discussed. Crash compatibility, mechanical defect, use of restraint device, roadside hazard, structure integrity, substandard crash barrier, superstructure and seat anchorage have been identified as injury factors, while conspicuousness, driving under the influence (DUI), fatigue, brake defect, overloading, risky driving, road defect, safety, health and environmental (SHE) compliance, speeding and tyre defect are classified as crash occurrence factors. Each case may result from several issues and thus, the numbers stated in the following tables do not refer to the number of investigated cases.
4.1 Fatalities
Table 20 presents the number of fatality per case by injury and crash occurrence factors. Crash compatibility, fatigue, risky driving and speeding (boxed in red) are the most critical factors to be addressed to reduce death due to road accidents because they cause more than three fatalities per case. No crash cases with zero fatality are recorded regarding superstructure or seat anchorage failure, driving under the influence (DUI), brake defect, and overloading factors. This means that crashes regarding
Table 19 Fatality and KSI indexes by lighting condition
Parameters Number of cases
Casualties Number of occupants
Index
Dark with lighting 55 Fatal 142 1.62
KSI 235 5.34
Dark without lighting
119 Fatal 337 2.67
KSI 529 4.60
Dawn/dusk 34 Fatal 88 2.08
KSI 166 7.44
Daylight 186 Fatal 466 2.48
KSI 797 5.45
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Table 20 Number of fatalities per case by injury and crash occurrence factors
Factor 0 1–3 >3 Total
Injury Count (% by column, % by row)
Crash compatibility
1(3.1,1.1) 68(13.2,74.7) 22(14.4,24.2) 91
Mech. defect/Other
1(3.1,3.6) 21(4.1,75) 6(3.9,21.4) 28
Use of restraint device
2(6.3,3.4) 44(8.6,74.6) 13(8.5,22) 59
Roadside hazard 3(9.4,8.8) 26(5.1,76.5) 5(3.3,14.7) 34
Structure integrity 1(3.1,5.9) 12(2.3,70.6) 4(2.6,23.5) 17
Substandard crash barrier
1(3.1,5.9) 12(2.3,70.6) 4(2.6,23.5) 17
Superstructure 0(0,0) 2(0.4,40) 3(2,60) 5
Seat anchorage 0(0,0) 3(0.6,100) 0(0,0) 3
Crash Count (% by column, % by row)
Conspicuousness 1(3.1,5.6) 12(2.3,66.7) 5(3.3,27.8) 18
DUI 0(0,0) 20(3.9,83.3) 4(2.6,16.7) 24
Fatigue 6(18.8,8.6) 44(8.6,62.9) 20(13.1,28.6) 70
Brake defect 0(0,0) 17(3.3,85) 3(2,15) 20
Overloading 0(0,0) 10(1.9,90.9) 1(0.7,9.1) 11
Risky driving 5(15.6,4.1) 93(18.1,76.9) 23(15,19) 121
Road defect 2(6.3,5.6) 27(5.3,75) 7(4.6,19.4) 36
SHE 4(12.5,10.5) 26(5.1,68.4) 8(5.2,21.1) 38
Speeding 3(9.4,3.2) 69(13.4,74.2) 21(13.7,22.6) 93
Tyre defect 2(6.3,14.3) 8(1.6,57.1) 4(2.6,28.6) 14
Total 32 514 153 699
these factors tend to cause severe consequences in terms of the number of fatalities.
4.2 Month of Occurrence
Referring to Table 21, the highest number of investigated cases is in December, with 81 cases. In that particular month, risky driving, crash compatibility, speeding, SHE compliance and fatigue are recorded as the most prominent factors of crash occurrence, which are 17.3%, 12.3%, 9.9%, 9.9% and 8.6%, respectively. The trend is similar throughout the year, especially for risky driving.
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Tabl
e 21
D
istr
ibut
ion
of in
jury
and
cra
sh o
ccur
renc
e fa
ctor
s by
mon
th o
f occ
urre
nce
Fact
ors
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Tota
l
Inju
ry
Coun
t (%
by
colu
mn,
% b
y ro
w)
Cra
sh
com
patib
ility
7(14
.6,7
.6)
8(16
.7,8
.7)
4(6.
6,4.
3)6(
10,6
.5)
7(13
.2,7
.6)
6(12
.5,6
.5)
10(1
6.9,
10.9
)8(
13.6
,8.7
)12
(18.
8,13
)6(
9.1,
6.5)
8(14
.8,8
.7)
10(1
2.3,
10.9
)92
Mec
h. d
efec
t/O
ther
1(2.
1,3.
6)2(
4.2,
7.1)
2(3.
3,7.
1)3(
5,10
.7)
0(0,
0)4(
8.3,
14.3
)1(
1.7,
3.6)
1(1.
7,3.
6)3(
4.7,
10.7
)3(
4.5,
10.7
)3(
5.6,
10.7
)5(
6.2,
17.9
)28
Use
of r
estr
aint
de
vice
5(10
.4,8
.5)
5(10
.4,8
.5)
8(13
.1,1
3.6)
4(6.
7,6.
8)8(
15.1
,13.
6)2(
4.2,
3.4)
3(5.
1,5.
1)8(
13.6
,13.
6)3(
4.7,
5.1)
5(7.
6,8.
5)5(
9.3,
8.5)
3(3.
7,5.
1)59
Road
side
haz
ard
1(2.
1,2.
9)1(
2.1,
2.9)
5(8.
2,14
.7)
3(5,
8.8)
3(5.
7,8.
8)3(
6.3,
8.8)
3(5.
1,8.
8)0(
0,0)
3(4.
7,8.
8)1(
1.5,
2.9)
5(9.
3,14
.7)
6(7.
4,17
.6)
34
Stru
ctur
e in
tegr
ity2(
4.2,
11.8
)1(
2.1,
5.9)
1(1.
6,5.
9)2(
3.3,
11.8
)2(
3.8,
11.8
)1(
2.1,
5.9)
1(1.
7,5.
9)1(
1.7,
5.9)
2(3.
1,11
.8)
1(1.
5,5.
9)1(
1.9,
5.9)
2(2.
5,11
.8)
17
Subs
tand
ard
cras
h ba
rrie
r1(
2.1,
5.9)
2(4.
2,11
.8)
2(3.
3,11
.8)
3(5,
17.6
)1(
1.9,
5.9)
2(4.
2,11
.8)
1(1.
7,5.
9)0(
0,0)
0(0,
0)0(
0,0)
1(1.
9,5.
9)4(
4.9,
23.5
)17
Supe
rstr
uctu
re1(
2.1,
20)
0(0,
0)1(
1.6,
20)
1(1.
7,20
)0(
0,0)
0(0,
0)1(
1.7,
20)
0(0,
0)0(
0,0)
0(0,
0)1(
1.9,
20)
0(0,
0)5
Seat
anc
hora
ge0(
0,0)
0(0,
0)1(
1.6,
33.3
)0(
0,0)
0(0,
0)0(
0,0)
0(0,
0)0(
0,0)
1(1.
6,33
.3)
0(0,
0)0(
0,0)
1(1.
2,33
.3)
3
Cras
h Co
unt (
% b
y co
lum
n, %
by
row
)
Cons
picu
ousn
ess
4(8.
3,22
.2)
0(0,
0)3(
4.9,
16.7
)2(
3.3,
11.1
)1(
1.9,
5.6)
0(0,
0)1(
1.7,
5.6)
2(3.
4,11
.1)
1(1.
6,5.
6)1(
1.5,
5.6)
1(1.
9,5.
6)2(
2.5,
11.1
)18
DU
I3(
6.3,
12.5
)1(
2.1,
4.2)
2(3.
3,8.
3)1(
1.7,
4.2)
2(3.
8,8.
3)2(
4.2,
8.3)
3(5.
1,12
.5)
4(6.
8,16
.7)
1(1.
6,4.
2)1(
1.5,
4.2)
2(3.
7,8.
3)2(
2.5,
8.3)
24
Fatig
ue3(
6.3,
4.3)
4(8.
3,5.
7)7(
11.5
,10)
8(13
.3,1
1.4)
9(17
,12.
9)3(
6.3,
4.3)
6(10
.2,8
.6)
9(15
.3,1
2.9)
6(9.
4,8.
6)6(
9.1,
8.6)
2(3.
7,2.
9)7(
8.6,
10)
70
Brak
e de
fect
1(2.
1,5)
3(6.
3,15
)0(
0,0)
1(1.
7,5)
1(1.
9,5)
3(6.
3,15
)3(
5.1,
15)
3(5.
1,15
)0(
0,0)
3(4.
5,15
)1(
1.9,
5)1(
1.2,
5)20
Ove
rload
ing
1(2.
1,9.
1)0(
0,0)
0(0,
0)1(
1.7,
9.1)
1(1.
9,9.
1)0(
0,0)
1(1.
7,9.
1)3(
5.1,
27.3
)0(
0,0)
2(3,
18.2
)2(
3.7,
18.2
)0(
0,0)
11
Risk
y dr
ivin
g5(
10.4
,4.1
)8(
16.7
,6.6
)10
(16.
4,8.
3)10
(16.
7,8.
3)6(
11.3
,5)
9(18
.8,7
.4)
15(2
5.4,
12.4
)11
(18.
6,9.
1)12
(18.
8,9.
9)14
(21.
2,11
.6)
7(13
,5.8
)14
(17.
3,11
.6)
121
Road
def
ect
6(12
.5,1
6.7)
2(4.
2,5.
6)3(
4.9,
8.3)
2(3.
3,5.
6)2(
3.8,
5.6)
0(0,
0)1(
1.7,
2.8)
0(0,
0)5(
7.8,
13.9
)5(
7.6,
13.9
)5(
9.3,
13.9
)5(
6.2,
13.9
)36
SHE
2(4.
2,5.
3)2(
4.2,
5.3)
3(4.
9,7.
9)4(
6.7,
10.5
)4(
7.5,
10.5
)2(
4.2,
5.3)
3(5.
1,7.
9)1(
1.7,
2.6)
3(4.
7,7.
9)5(
7.6,
13.2
)1(
1.9,
2.6)
8(9.
9,21
.1)
38
Spee
ding
4(8.
3,4.
3)9(
18.8
,9.6
)8(
13.1
,8.5
)9(
15,9
.6)
5(9.
4,5.
3)10
(20.
8,10
.6)
4(6.
8,4.
3)7(
11.9
,7.4
)10
(15.
6,10
.6)
11(1
6.7,
11.7
)9(
16.7
,9.6
)8(
9.9,
8.5)
94
Tyre
def
ect
1(2.
1,7.
1)0(
0,0)
1(1.
6,7.
1)0(
0,0)
1(1.
9,7.
1)1(
2.1,
7.1)
2(3.
4,14
.3)
1(1.
7,7.
1)2(
3.1,
14.3
)2(
3,14
.3)
0(0,
0)3(
3.7,
21.4
)14
Tota
l48
4861
6053
4859
5964
6654
8170
1
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
44
4.3 Time of Occurrence
Table 22 displays injury and crash occurrence factors as a function of time of occurrence. It is observed that a quarter of the crashes (25%) occurred during the wee hours, which is defined as the period between 12:00 a.m. until 6:00 a.m. Factors related to fatigue (47.8%), driving under the influence (41.7%) and conspicuousness (35.7%) are remarkably high during that time frame.
Table 22 Distribution of injury and crash occurrence factors by time of occurrence
Factors 00:01–6:00 6:01–9:00 9:01–12:00 12:01–14:00
14:01–16:00
16:01–20:00
20:01–24:00
Total
Injury Count (% by column, % by row)
Crash compatibility
11(6.4,12) 18(19.1,19.6) 14(14.6,15.2) 10(15.2,10.9) 8(13.3,8.7) 15(13.9,16.3) 16(18.2,17.4) 92
Mech. defect/Other
7(4.1,25) 5(5.3,17.9) 4(4.2,14.3) 1(1.5,3.6) 2(3.3,7.1) 3(2.8,10.7) 6(6.8,21.4) 28
Use of restraint device
11(6.4,18.6) 3(3.2,5.1) 11(11.5,18.6) 5(7.6,8.5) 5(8.3,8.5) 15(13.9,25.4) 9(10.2,15.3) 59
Roadside hazard 9(5.3,27.3) 7(7.4,21.2) 3(3.1,9.1) 4(6.1,12.1) 4(6.7,12.1) 3(2.8,9.1) 3(3.4,9.1) 33
Structure integrity
6(3.5,35.3) 3(3.2,17.6) 2(2.1,11.8) 2(3,11.8) 2(3.3,11.8) 0(0,0) 2(2.3,11.8) 17
Substandard crash barrier
4(2.3,33.3) 4(4.3,33.3) 1(1,8.3) 1(1.5,8.3) 1(1.7,8.3) 1(0.9,8.3) 0(0,0) 12
Superstructure 1(0.6,20) 2(2.1,40) 0(0,0) 0(0,0) 1(1.7,20) 0(0,0) 1(1.1,20) 5
Seat anchorage 3(1.8,100) 0(0,0) 0(0,0) 0(0,0) 0(0,0) 0(0,0) 0(0,0) 3
Crash Count (% by column, % by row)
Conspicuousness 5(2.9,35.7) 1(1.1,7.1) 3(3.1,21.4) 3(4.5,21.4) 1(1.7,7.1) 0(0,0) 1(1.1,7.1) 14
DUI 10(5.8,41.7) 4(4.3,16.7) 1(1,4.2) 2(3,8.3) 1(1.7,4.2) 2(1.9,8.3) 4(4.5,16.7) 24
Fatigue 33(19.3,47.8) 9(9.6,13) 4(4.2,5.8) 7(10.6,10.1) 4(6.7,5.8) 8(7.4,11.6) 4(4.5,5.8) 69
Brake defect 4(2.3,20) 3(3.2,15) 4(4.2,20) 2(3,10) 2(3.3,10) 3(2.8,15) 2(2.3,10) 20
Overloading 3(1.8,27.3) 0(0,0) 4(4.2,36.4) 1(1.5,9.1) 2(3.3,18.2) 1(0.9,9.1) 0(0,0) 11
Risky driving 18(10.5,15.4) 14(14.9,12) 19(19.8,16.2) 15(22.7,12.8) 12(20,10.3) 19(17.6,16.2) 20(22.7,17.1) 117
Road defect 7(4.1,19.4) 4(4.3,11.1) 5(5.2,13.9) 2(3,5.6) 4(6.7,11.1) 10(9.3,27.8) 4(4.5,11.1) 36
SHE 13(7.6,36.1) 6(6.4,16.7) 2(2.1,5.6) 4(6.1,11.1) 2(3.3,5.6) 7(6.5,19.4) 2(2.3,5.6) 36
Speeding 23(13.5,24.7) 10(10.6,10.8) 17(17.7,18.3) 4(6.1,4.3) 7(11.7,7.5) 20(18.5,21.5) 12(13.6,12.9) 93
Tyre defect 3(1.8,21.4) 1(1.1,7.1) 2(2.1,14.3) 3(4.5,21.4) 2(3.3,14.3) 1(0.9,7.1) 2(2.3,14.3) 14
Total 171 94 96 66 60 108 88 683
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
45
Most casualties related to use of restraint device are observed on crashes that occurred after office hours until dawn, which constitute 59.3% of the total number of crashes according to use of restraint device. High number of cases related to roadside hazard can be noticed beginning from mid night until 9:00 a.m., while speeding records high number of cases that occurred during wee hours and after office hours. Crashes due to risky driving are scattered evenly in all time periods. This illustrates that risky driving is a crash factor regardless of time of occurrence.
4.4 Crash Type
Table 23 displays injury and crash occurrence factors by types of crash. Head-on collisions account for the highest frequency of crashes in terms of crash compatibility factor (17.6%). It is also important to highlight the high percentage of rear impact collision in crash compatibility factor (28.6%). In terms of crash occurrence as a function of collision type, risky driving accounts of the highest percentage (17.5%). For head-on collisions, 27.6% of cases are attributed to risky driving. From the table, it is concluded that more than a quarter of hitting object collision cases involved speeding (18%), roadside hazard (15%) and fatigue (11.4%).
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
46
Fact
ors
Hea
d-on
Hit
ting
an
imal
Hit
ting
ob
ject
Hit
ting
pe
dest
rian
Mul
tipl
e ev
ent
Rear
im
pact
Rollo
ver
Side
impa
ctSi
de
swep
tTo
tal
Inju
ry
Coun
t (%
by
colu
mn,
% b
y ro
w)
Cra
sh c
ompa
tibili
ty37
(17.
6,40
.7)
0(0,
0)0(
0,0)
0(0,
0)12
(14.
3,13
.2)
26(2
8.6,
28.6
)2(
7.7,
2.2)
14(1
5.2,
15.4
)0(
0,0)
91
Mec
h. d
efec
t/O
ther
9(4.
3,33
.3)
0(0,
0)8(
4.8,
29.6
)1(
16.7
,3.7
)3(
3.6,
11.1
)4(
4.4,
14.8
)0(
0,0)
2(2.
2,7.
4)0(
0,0)
27
Use
of r
estr
aint
de
vice
24(1
1.4,
41.4
)0(
0,0)
15(9
,25.
9)0(
0,0)
3(3.
6,5.
2)2(
2.2,
3.4)
0(0,
0)13
(14.
1,22
.4)
1(8.
3,1.
7)58
Road
side
haz
ard
0(0,
0)1(
50,2
.9)
25(1
5,73
.5)
0(0,
0)2(
2.4,
5.9)
4(4.
4,11
.8)
0(0,
0)2(
2.2,
5.9)
0(0,
0)34
Stru
ctur
e in
tegr
ity7(
3.3,
41.2
)0(
0,0)
5(3,
29.4
)0(
0,0)
3(3.
6,17
.6)
1(1.
1,5.
9)0(
0,0)
1(1.
1,5.
9)0(
0,0)
17
Subs
tand
ard
cras
h ba
rrie
r1(
0.5,
5.9)
0(0,
0)12
(7.2
,70.
6)0(
0,0)
1(1.
2,5.
9)0(
0,0)
2(7.
7,11
.8)
1(1.
1,5.
9)0(
0,0)
17
Supe
rstr
uctu
re1(
0.5,
20)
0(0,
0)0(
0,0)
0(0,
0)1(
1.2,
20)
2(2.
2,40
)0(
0,0)
1(1.
1,20
)0(
0,0)
5
Seat
anc
hora
ge0(
0,0)
0(0,
0)1(
0.6,
33.3
)0(
0,0)
0(0,
0)1(
1.1,
33.3
)0(
0,0)
1(1.
1,33
.3)
0(0,
0)3
Cras
h Co
unt (
% b
y co
lum
n, %
by
row
)
Cons
picu
ousn
ess
3(1.
4,18
.8)
0(0,
0)3(
1.8,
18.8
)1(
16.7
,6.3
)2(
2.4,
12.5
)4(
4.4,
25)
1(3.
8,6.
3)2(
2.2,
12.5
)0(
0,0)
16
DU
I6(
2.9,
26.1
)0(
0,0)
6(3.
6,26
.1)
0(0,
0)5(
6,21
.7)
3(3.
3,13
)2(
7.7,
8.7)
1(1.
1,4.
3)0(
0,0)
23
Fatig
ue15
(7.1
,21.
4)0(
0,0)
19(1
1.4,
27.1
)1(
16.7
,1.4
)11
(13.
1,15
.7)
13(1
4.3,
18.6
)6(
23.1
,8.6
)4(
4.3,
5.7)
1(8.
3,1.
4)70
Brak
e de
fect
8(3.
8,42
.1)
0(0,
0)5(
3,26
.3)
0(0,
0)3(
3.6,
15.8
)1(
1.1,
5.3)
0(0,
0)2(
2.2,
10.5
)0(
0,0)
19
Ove
rload
ing
4(1.
9,36
.4)
0(0,
0)2(
1.2,
18.2
)0(
0,0)
0(0,
0)0(
0,0)
2(7.
7,18
.2)
3(3.
3,27
.3)
0(0,
0)11
Risk
y dr
ivin
g58
(27.
6,47
.9)
1(50
,0.8
)12
(7.2
,9.9
)1(
16.7
,0.8
)16
(19,
13.2
)9(
9.9,
7.4)
3(11
.5,2
.5)
15(1
6.3,
12.4
)6(
50,5
)12
1
Road
def
ect
9(4.
3,27
.3)
0(0,
0)13
(7.8
,39.
4)1(
16.7
,3)
4(4.
8,12
.1)
0(0,
0)0(
0,0)
5(5.
4,15
.2)
1(8.
3,3)
33
SHE
6(2.
9,15
.8)
0(0,
0)6(
3.6,
15.8
)1(
16.7
,2.6
)6(
7.1,
15.8
)12
(13.
2,31
.6)
3(11
.5,7
.9)
4(4.
3,10
.5)
0(0,
0)38
Spee
ding
20(9
.5,2
1.5)
0(0,
0)30
(18,
32.3
)0(
0,0)
11(1
3.1,
11.8
)8(
8.8,
8.6)
5(19
.2,5
.4)
18(1
9.6,
19.4
)1(
8.3,
1.1)
93
Tyre
def
ect
2(1,
14.3
)0(
0,0)
5(3,
35.7
)0(
0,0)
1(1.
2,7.
1)1(
1.1,
7.1)
0(0,
0)3(
3.3,
21.4
)2(
16.7
,14.
3)14
Tota
l21
02
167
684
9126
9212
690
Tabl
e 23
In
jury
and
cra
sh o
ccur
renc
e fa
ctor
s by
cra
sh ty
pe
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
47
4.5 Vehicle Type
Table 24 shows injury and crash occurrence factors according to vehicle type. In terms of injury, crash compatibility and use of restraint device contribute the highest percentage of passenger car crashes (14.7% and 9.8%). High percentage of crash compatibility related cases is also identified in crashes involving lorries and buses (22.4% and 7.9%).
In terms of crash occurrence, the data support that risky driving and fatigue are the highest causes of crash. Fatigue accounts for 7.7% of crashes involving passenger cars, 9.9% lorry and 7.9% bus. Risky driving accounts for 18% of the number of cases involving passenger cars. It is also important to note that 15.3% of cases involving passenger cars are related to speeding.
Factors Car Lorry Bus Other Total
Injury Count (% by column, % by row)
Crash compatibility 80(14.7,44.4) 68(22.4,37.8) 22(7.9,12.2) 10(21.3,5.6) 180
Mech. defect/Other 25(4.6,69.4) 7(2.3,19.4) 4(1.4,11.1) 0(0,0) 36
Use of restraint device
53(9.8,67.1) 18(5.9,22.8) 5(1.8,6.3) 3(6.4,3.8) 79
Roadside hazard 26(4.8,61.9) 7(2.3,16.7) 8(2.9,19) 1(2.1,2.4) 42
Structure integrity 10(1.8,37) 9(3,33.3) 8(2.9,29.6) 0(0,0) 27
Substandard crash barrier
9(1.7,40.9) 5(1.7,22.7) 7(2.5,31.8) 1(2.1,4.5) 22
Superstructure 4(0.7,44.4) 3(1,33.3) 1(0.4,11.1) 1(2.1,11.1) 9
Seat anchorage 2(0.4,40) 1(0.3,20) 2(0.7,40) 0(0,0) 5
Crash Count (% by column, % by row)
Conspicuousness 14(2.6,53.8) 8(2.6,30.8) 4(1.4,15.4) 0(0,0) 26
DUI 18(3.3,60) 5(1.7,16.7) 7(2.5,23.3) 0(0,0) 30
Fatigue 42(7.7,43.3) 30(9.9,30.9) 22(7.9,22.7) 3(6.4,3.1) 97
Brake defect 15(2.8,50) 10(3.3,33.3) 5(1.8,16.7) 0(0,0) 30
Overloading 8(1.5,6.5) 4(1.3,3.2) 109(39.4,87.9) 3(6.4,2.4) 124
Risky driving 98(18,60.1) 49(16.2,30.1) 0(0,0) 16(34,9.8) 163
Road defect 30(5.5,44.8) 8(2.6,11.9) 27(9.7,40.3) 2(4.3,3) 67
SHE 13(2.4,24.5) 29(9.6,54.7) 8(2.9,15.1) 3(6.4,5.7) 53
Speeding 83(15.3,58) 37(12.2,25.9) 20(7.2,14) 3(6.4,2.1) 143
Tyre defect 13(2.4,35.1) 5(1.7,13.5) 18(6.5,48.6) 1(2.1,2.7) 37
Total 543 303 277 47 1170
Table 24 Injury and crash occurrence factors by vehicle type
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
48
4.6 Number of Vehicles Involved
Table 25 depicts injury and crash occurrence factors according to the number of vehicles involved. For injury, crash compatibility factor accounts for the highest percentage involving both single vehicle and two-vehicle collisions (16% and 12.8%). A substantial number of cases involving single and two vehicles are also identified to be related to use of restraint device factor (9.4% and 7.3%).
Table 25 Injury and crash occurrence factors by number of vehicles involved
Factors Single vehicle
Two vehicles Multiple vehicles
Total
Injury Count (% by column, % by row)Crash compatibility 34(16,37.4) 49(12.8,53.8) 8(7.9,8.8) 91
Mech. defect/Other 9(4.2,32.1) 14(3.7,50) 5(5,17.9) 28
Use of restraint device 20(9.4,34.5) 28(7.3,48.3) 10(9.9,17.2) 58
Roadside hazard 10(4.7,29.4) 20(5.2,58.8) 4(4,11.8) 34
Structure integrity 4(1.9,25) 9(2.3,56.3) 3(3,18.8) 16
Substandard crash barrier 4(1.9,23.5) 9(2.3,52.9) 4(4,23.5) 17
Superstructure 4(1.9,80) 1(0.3,20) 0(0,0) 5
Seat anchorage 0(0,0) 3(0.8,100) 0(0,0) 3
Crash Count (% by column, % by row)Conspicuousness 3(1.4,16.7) 9(2.3,50) 6(5.9,33.3) 18
DUI 6(2.8,25) 16(4.2,66.7) 2(2,8.3) 24
Fatigue 20(9.4,28.6) 39(10.2,55.7) 11(10.9,15.7) 70
Brake defect 4(1.9,20) 14(3.7,70) 2(2,10) 20
Overloading 5(2.4,45.5) 2(0.5,18.2) 4(4,36.4) 11
Risky driving 35(16.5,29.4) 70(18.3,58.8) 14(13.9,11.8) 119
Road defect 15(7.1,41.7) 16(4.2,44.4) 5(5,13.9) 36
SHE 11(5.2,28.9) 21(5.5,55.3) 6(5.9,15.8) 38
Speeding 22(10.4,23.4) 56(14.6,59.6) 16(15.8,17) 94
Tyre defect 6(2.8,42.9) 7(1.8,50) 1(1,7.1) 14
Total 212 383 101 696
Risky driving, fatigue and speeding are identified as major contributors of crash. More than 10% of the number of cases involving single, two and multiple vehicles are related to risky driving (16.5%, 18.3% and 13.9%).
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
49
4.7 Road Type
Table 26 shows injury and crash occurrence factors according to road type. Crash compatibility is identified as a major contributor to injury in crashes occurring on federal and state roads (13.7% and 13.5%). Use of restraint device is also identified as one factor that leads to higher injury in crashes occurring on federal and state roads (9.0% and 12.6%).
Table 26 Injury and crash occurrence factors by road type
Factors Municipal Expressway Federal Private State Total
Injury Count (% by column, % by row)
Crash compatibility 1(100,1.1) 22(11.1,24.7) 38(13.7,42.7) 0(0,0) 28(13.5,31.5) 89
Mech. defect/Other 0(0,0) 7(3.5,25) 13(4.7,46.4) 0(0,0) 8(3.9,28.6) 28
Use of restraint device
0(0,0) 6(3,10.3) 25(9,43.1) 1(33.3,1.7) 26(12.6,44.8) 58
Roadside hazard 0(0,0) 10(5.1,29.4) 14(5,41.2) 0(0,0) 10(4.8,29.4) 34
Structure integrity 0(0,0) 6(3,35.3) 6(2.2,35.3) 0(0,0) 5(2.4,29.4) 17
Substandard crash barrier
0(0,0) 12(6.1,75) 3(1.1,18.8) 0(0,0) 1(0.5,6.3) 16
Superstructure 0(0,0) 2(1,40) 1(0.4,20) 0(0,0) 2(1,40) 5
Seat anchorage 0(0,0) 1(0.5,33.3) 1(0.4,33.3) 0(0,0) 1(0.5,33.3) 3
Crash Count (% by column, % by row)
Conspicuousness 0(0,0) 5(2.5,27.8) 12(4.3,66.7) 0(0,0) 1(0.5,5.6) 18
DUI 0(0,0) 5(2.5,21.7) 10(3.6,43.5) 0(0,0) 8(3.9,34.8) 23
Fatigue 0(0,0) 33(16.7,48.5) 25(9,36.8) 0(0,0) 10(4.8,14.7) 68
Brake defect 0(0,0) 6(3,30) 8(2.9,40) 0(0,0) 6(2.9,30) 20
Overloading 0(0,0) 3(1.5,27.3) 5(1.8,45.5) 0(0,0) 3(1.4,27.3) 11
Risky driving 0(0,0) 17(8.6,14.4) 56(20.1,47.5) 0(0,0) 45(21.7,38.1) 118
Road defect 0(0,0) 6(3,16.7) 14(5,38.9) 1(33.3,2.8) 15(7.2,41.7) 36
SHE 0(0,0) 19(9.6,51.4) 9(3.2,24.3) 0(0,0) 9(4.3,24.3) 37
Speeding 0(0,0) 35(17.7,38) 31(11.2,33.7) 1(33.3,1.1) 25(12.1,27.2) 92
Tyre defect 0(0,0) 3(1.5,21.4) 7(2.5,50) 0(0,0) 4(1.9,28.6) 14
Total 1 198 278 3 207 687
In term of crash occurrence, the data supports that risky driving, fatigue and speeding are among the major contributors of crash. Fatigue accounts for 16.7% of crashes on expressways and 9.0% for crashes on federal roads. Risky driving accounts for 20.1% of the number of crashes on federal roads and 21.7% on state roads.
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It is also important to note that 17.7% of crashes on expressway are related to speeding.
4.8 Intersection Type
Table 27 depicts injury and crash occurrence factors according to intersection type. For injury, crash compatibility accounts for the highest percentage of crashes occurring at both midblock and T-junctions (12.8% and 21.3%). A substantial number of cases occurring at midblock is also identified to be related to use of restraint device factor (9.3%).
Table 27 Injury and crash occurrence factors by intersection type
Factors Crossroad Midblock Staggered junction
T-Junction Y-Junction Total
Injury Count (% by column, % by row)Crash compatibility 2(20,2.4) 66(12.8,78.6) 4(8.2,4.8) 10(21.3,11.9) 2(4.7,2.4) 84
Mech. defect/Other 0(0,0) 23(4.4,88.5) 0(0,0) 3(6.4,11.5) 0(0,0) 26
Use of restraint device
2(20,3.5) 48(9.3,84.2) 1(2,1.8) 5(10.6,8.8) 1(2.3,1.8) 57
Roadside hazard 0(0,0) 28(5.4,90.3) 0(0,0) 0(0,0) 3(7,9.7) 31
Structure integrity 1(10,6.3) 13(2.5,81.3) 0(0,0) 2(4.3,12.5) 0(0,0) 16
Substandard crash barrier
0(0,0) 17(3.3,100) 0(0,0) 0(0,0) 0(0,0) 17
Superstructure 0(0,0) 4(0.8,80) 0(0,0) 1(2.1,20) 0(0,0) 5
Seat anchorage 0(0,0) 3(0.6,100) 0(0,0) 0(0,0) 0(0,0) 3
Crash Count (% by column, % by row)Conspicuousness 0(0,0) 14(2.7,87.5) 0(0,0) 2(4.3,12.5) 0(0,0) 16
DUI 0(0,0) 20(3.9,90.9) 0(0,0) 1(2.1,4.5) 1(2.3,4.5) 22
Fatigue 2(20,2.9) 65(12.6,92.9) 1(2,1.4) 1(2.1,1.4) 1(2.3,1.4) 70
Brake defect 0(0,0) 17(3.3,94.4) 0(0,0) 1(2.1,5.6) 0(0,0) 18
Overloading 0(0,0) 9(1.7,81.8) 0(0,0) 1(2.1,9.1) 1(2.3,9.1) 11
Risky driving 1(10,0.9) 94(18.2,81) 2(4.1,1.7) 15(31.9,12.9) 4(9.3,3.4) 116
Road defect 2(20,6.3) 26(5,81.3) 1(2,3.1) 2(4.3,6.3) 1(2.3,3.1) 32
SHE 0(0,0) 32(6.2,88.9) 2(4.1,5.6) 2(4.3,5.6) 0(0,0) 36
Speeding 0(0,0) 35(6.8,38) 31(63.3,33.7) 1(2.1,1.1) 25(58.1,27.2) 92
Tyre defect 0(0,0) 3(0.6,21.4) 7(14.3,50) 0(0,0) 4(9.3,28.6) 14
Total 10 517 49 47 43 666
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Risky driving, fatigue and speeding are identified as major contributors to crash occurrence. More than 10% of cases occurring at midblock are related to fatigue and risky driving (12.6% and 18.2%). A substantial number of cases occurring at staggered and Y-junctions are related to speeding.
4.9 Horizontal Profile of the Road
Table 28 shows injury and crash occurrence factors according to horizontal road profile. Crash compatibility is identified as a major contributor to injury for crashes occurring at curve and straight roads (11.2% and 14.2%). Use of restraint device is also identified as one factor that leads to higher injury in crashes at curve and straight roads (8.1% and 8.5%).
Table 28 Injury and crash occurrence factors by horizontal profile of the road
Factors Curve Straight TotalInjury Count (% by column, % by row)Crash compatibility 29(11.2,32.6) 60(14.2,67.4) 89
Mech. defect/Other 8(3.1,28.6) 20(4.7,71.4) 28
Use of restraint device 21(8.1,36.8) 36(8.5,63.2) 57
Roadside hazard 10(3.8,29.4) 24(5.7,70.6) 34
Structure integrity 8(3.1,50) 8(1.9,50) 16
Substandard crash barrier 9(3.5,52.9) 8(1.9,47.1) 17
Superstructure 0(0,0) 5(1.2,100) 5
Seat anchorage 0(0,0) 3(0.7,100) 3
Crash Count (% by column, % by row)Conspicuousness 5(1.9,31.3) 11(2.6,68.8) 16
DUI 10(3.8,41.7) 14(3.3,58.3) 24
Fatigue 23(8.8,32.9) 47(11.1,67.1) 70
Brake defect 7(2.7,38.9) 11(2.6,61.1) 18
Overloading 5(1.9,45.5) 6(1.4,54.5) 11
Risky driving 49(18.8,41.9) 68(16,58.1) 117
Road defect 13(5,36.1) 23(5.4,63.9) 36
SHE 10(3.8,27.8) 26(6.1,72.2) 36
Speeding 46(17.7,49.5) 47(11.1,50.5) 93
Tyre defect 7(2.7,50) 7(1.7,50) 14
Total 260 424 684
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In term of crash occurrence, the data support that risky driving, fatigue and speeding are among the major contributors of crash. Fatigue accounts for 8.8% of crashes occurring at curve roads and 11.1% of crashes at straight roads. Risky driving accounts for 18.8% of the number of crashes on curve roads and 16% on straight roads. It is also important to note that 17.7% crashes on curve roads and 11.1% of crashes on straight roads are related to speeding.
4.10 Vertical Profile of the Road
Table 29 shows injury and crash occurrence factors according to vertical road profile. Crash compatibility is identified as a major contributor to injury for crashes on flat and sloping roads (13.5% and 11.6%). Use of restraint device is also identified as one factor that leads to higher injury for crashes on flat and sloping roads (8% and 9.1%).
In terms of crash occurrence, the data support that risky driving and fatigue are the major contributors of crash. Risky driving accounts for 15.4% of the number of cases on flat roads and 21.2% on slope roads. It is also important to note that 13.7% of crashes on flat roads and 14.1% of crashes on sloping roads are related to speeding.
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Table 29 Injury and crash occurrence factors by vertical profile of the road
Factors Flat Slope TotalInjury Count (% by column, % by row)Crash compatibility 64(13.5,73.6) 23(11.6,26.4) 87
Mech. defect/Other 18(3.8,66.7) 9(4.5,33.3) 27
Use of restraint device 38(8,67.9) 18(9.1,32.1) 56
Roadside hazard 23(4.9,71.9) 9(4.5,28.1) 32
Structure integrity 13(2.7,81.3) 3(1.5,18.8) 16
Substandard crash barrier 12(2.5,70.6) 5(2.5,29.4) 17
Superstructure 3(0.6,60) 2(1,40) 5
Seat anchorage 3(0.6,100) 0(0,0) 3
Crash Count (% by column, % by row)Conspicuousness 8(1.7,57.1) 6(3,42.9) 14
DUI 17(3.6,77.3) 5(2.5,22.7) 22
Fatigue 51(10.8,73.9) 18(9.1,26.1) 69
Brake defect 15(3.2,83.3) 3(1.5,16.7) 18
Overloading 8(1.7,72.7) 3(1.5,27.3) 11
Risky driving 73(15.4,63.5) 42(21.2,36.5) 115
Road defect 22(4.7,61.1) 14(7.1,38.9) 36
SHE 27(5.7,75) 9(4.5,25) 36
Speeding 65(13.7,69.9) 28(14.1,30.1) 93
Tyre defect 13(2.7,92.9) 1(0.5,7.1) 14
Total 473 198 671
4.11 Carriageway Type
Table 30 depicts injury and crash occurrence factors according to carriageway type. The number of investigated cases at single carriageway is 71 cases higher than those at dual carriageway. Injuries due to use of restraint device are much prominent for crashes at single carriageway while seat anchorage failures are much prominent for crashes at dual carriageway. In terms of crash occurrence, DUI, overloading and risky driving are more prominent factors for crashes at single carriageway while cases related to fatigue, SHE compliance and speeding are higher at dual carriageway accidents.
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Factors Single Dual Total
Injury Count (% by column, % by row)
Crash compatibility 49(12.9,55.1) 40(13,44.9) 89
Mech. defect/Other 13(3.4,46.4) 15(4.9,53.6) 28
Use of restraint device 43(11.3,72.9) 16(5.2,27.1) 59
Roadside hazard 14(3.7,42.4) 19(6.2,57.6) 33
Structure integrity 8(2.1,50) 8(2.6,50) 16
Substandard crash barrier 7(1.8,41.2) 10(3.2,58.8) 17
Superstructure 2(0.5,40) 3(1,60) 5
Seat anchorage 1(0.3,33.3) 2(0.6,66.7) 3
Crash Count (% by column, % by row)
Conspicuousness 7(1.8,50) 7(2.3,50) 14
DUI 15(4,65.2) 8(2.6,34.8) 23
Fatigue 30(7.9,42.9) 40(13,57.1) 70
Brake defect 11(2.9,57.9) 8(2.6,42.1) 19
Overloading 7(1.8,63.6) 4(1.3,36.4) 11
Risky driving 86(22.7,71.7) 34(11,28.3) 120
Road defect 21(5.5,58.3) 15(4.9,41.7) 36
SHE 12(3.2,33.3) 24(7.8,66.7) 36
Speeding 46(12.1,48.9) 48(15.6,51.1) 94
Tyre defect 7(1.8,50) 7(2.3,50) 14
Total 379 308 687
4.12 Vicinity Area
Table 31 depicts injury and crash occurrence factors according to vicinity area of the crashes. The highest number of investigated cases is recorded at wooded area with 312 crash cases, almost half (46.7%) of the total cases. This is followed by crashes occurring at residential areas (112 cases or 16.8%) and agricultural areas (106 cases or 15.9%). For both injury and crash occurrence factors, similar trend of cases distribution can be observed. The main contributing factor of injuries for the cases according to vicinity area are crash compatibility and use of restraint device, while risky driving, speeding and fatigue are major contributors of crash occurrence.
Table 30 Injury and crash occurrence factors by carriageway type
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Tabl
e 31
In
jury
and
cra
sh o
ccur
renc
e fa
ctor
s by
vic
inity
are
a
Fact
ors
Agr
icul
tura
lBr
idge
Cons
truc
tion
Indu
stri
alM
ixRe
side
ntia
lSc
hool
Shop
lot
Woo
ded
area
Tota
l
Inju
ry
Coun
t (%
by
colu
mn,
% b
y ro
w)
Cra
sh c
ompa
tibili
ty15
(14.
2,17
.4)
1(6.
3,1.
2)2(
9.5,
2.3)
6(26
.1,7
)5(
16.7
,5.8
)12
(10.
7,14
)1(
16.7
,1.2
)7(
16.7
,8.1
)37
(11.
9,43
)86
Mec
h. d
efec
t/O
ther
5(4.
7,17
.9)
1(6.
3,3.
6)1(
4.8,
3.6)
0(0,
0)3(
10,1
0.7)
2(1.
8,7.
1)0(
0,0)
1(2.
4,3.
6)15
(4.8
,53.
6)28
Use
of r
estr
aint
dev
ice
11(1
0.4,
18.6
)0(
0,0)
2(9.
5,3.
4)2(
8.7,
3.4)
2(6.
7,3.
4)11
(9.8
,18.
6)1(
16.7
,1.7
)3(
7.1,
5.1)
27(8
.7,4
5.8)
59
Road
side
haz
ard
3(2.
8,9.
4)1(
6.3,
3.1)
2(9.
5,6.
3)0(
0,0)
2(6.
7,6.
3)5(
4.5,
15.6
)0(
0,0)
2(4.
8,6.
3)17
(5.4
,53.
1)32
Stru
ctur
e in
tegr
ity3(
2.8,
20)
0(0,
0)1(
4.8,
6.7)
0(0,
0)3(
10,2
0)3(
2.7,
20)
0(0,
0)1(
2.4,
6.7)
4(1.
3,26
.7)
15
Subs
tand
ard
cras
h ba
rrie
r0(
0,0)
4(25
,25)
0(0,
0)1(
4.3,
6.3)
2(6.
7,12
.5)
1(0.
9,6.
3)0(
0,0)
2(4.
8,12
.5)
6(1.
9,37
.5)
16
Supe
rstr
uctu
re1(
0.9,
20)
1(6.
3,20
)0(
0,0)
0(0,
0)0(
0,0)
0(0,
0)0(
0,0)
1(2.
4,20
)2(
0.6,
40)
5
Seat
anc
hora
ge1(
0.9,
33.3
)0(
0,0)
0(0,
0)0(
0,0)
0(0,
0)0(
0,0)
0(0,
0)0(
0,0)
2(0.
6,66
.7)
3
Cras
h Co
unt (
% b
y co
lum
n, %
by
row
)Co
nspi
cuou
snes
s1(
0.9,
7.1)
0(0,
0)1(
4.8,
7.1)
0(0,
0)0(
0,0)
4(3.
6,28
.6)
0(0,
0)1(
2.4,
7.1)
7(2.
2,50
)14
DU
I6(
5.7,
27.3
)0(
0,0)
1(4.
8,4.
5)0(
0,0)
2(6.
7,9.
1)3(
2.7,
13.6
)0(
0,0)
2(4.
8,9.
1)8(
2.6,
36.4
)22
Fatig
ue13
(12.
3,18
.8)
1(6.
3,1.
4)2(
9.5,
2.9)
5(21
.7,7
.2)
2(6.
7,2.
9)11
(9.8
,15.
9)0(
0,0)
2(4.
8,2.
9)33
(10.
6,47
.8)
69
Brak
e de
fect
6(5.
7,33
.3)
0(0,
0)0(
0,0)
1(4.
3,5.
6)1(
3.3,
5.6)
2(1.
8,11
.1)
0(0,
0)0(
0,0)
8(2.
6,44
.4)
18
Ove
rload
ing
2(1.
9,18
.2)
0(0,
0)0(
0,0)
0(0,
0)0(
0,0)
3(2.
7,27
.3)
0(0,
0)1(
2.4,
9.1)
5(1.
6,45
.5)
11
Risk
y dr
ivin
g18
(17,
15.5
)2(
12.5
,1.7
)3(
14.3
,2.6
)3(
13,2
.6)
3(10
,2.6
)29
(25.
9,25
)1(
16.7
,0.9
)4(
9.5,
3.4)
53(1
7,45
.7)
116
Road
def
ect
5(4.
7,14
.7)
1(6.
3,2.
9)4(
19,1
1.8)
1(4.
3,2.
9)1(
3.3,
2.9)
6(5.
4,17
.6)
1(16
.7,2
.9)
1(2.
4,2.
9)14
(4.5
,41.
2)34
SHE
2(1.
9,5.
7)2(
12.5
,5.7
)1(
4.8,
2.9)
2(8.
7,5.
7)3(
10,8
.6)
3(2.
7,8.
6)1(
16.7
,2.9
)2(
4.8,
5.7)
19(6
.1,5
4.3)
35
Spee
ding
12(1
1.3,
13)
2(12
.5,2
.2)
1(4.
8,1.
1)1(
4.3,
1.1)
1(3.
3,1.
1)15
(13.
4,16
.3)
1(16
.7,1
.1)
10(2
3.8,
10.9
)49
(15.
7,53
.3)
92
Tyre
def
ect
2(1.
9,15
.4)
0(0,
0)0(
0,0)
1(4.
3,7.
7)0(
0,0)
2(1.
8,15
.4)
0(0,
0)2(
4.8,
15.4
)6(
1.9,
46.2
)13
Tota
l10
616
2123
3011
26
4231
266
8
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4.13 Weather Condition
Table 32 shows injury and crash occurrence factors according to weather conditions. Critical crash cases that have been investigated by MIROS indicate 497 crashes occurred on fine days, which is 75.3% of the total cases. A significant number of crashes during good weather condition is related to crash compatibility, mechanical defect, roadside hazard and substandard crash barrier. When the crashes took place on rainy days, crash compatibility became worse, and the number of crashes increased to 19.3%.
Factors Drizzling Fine Foggy Raining TotalInjury Count (% by column, % by row)Crash compatibility 3(7.1,3.6) 64(12.9,77.1) 0(0,0) 16(13.9,19.3) 83
Mech. defect/Other 2(4.8,7.1) 25(5,89.3) 0(0,0) 1(0.9,3.6) 28
Use of restraint device 3(7.1,5.2) 40(8,69) 0(0,0) 15(13,25.9) 58
Roadside hazard 3(7.1,9.4) 25(5,78.1) 0(0,0) 4(3.5,12.5) 32
Structure integrity 1(2.4,6.3) 11(2.2,68.8) 0(0,0) 4(3.5,25) 16
Substandard crash barrier 1(2.4,6.3) 12(2.4,75) 1(16.7,6.3) 2(1.7,12.5) 16
Superstructure 1(2.4,25) 1(0.2,25) 0(0,0) 2(1.7,50) 4
Seat anchorage 0(0,0) 2(0.4,66.7) 0(0,0) 1(0.9,33.3) 3
Crash Count (% by column, % by row)Conspicuousness 0(0,0) 13(2.6,92.9) 0(0,0) 1(0.9,7.1) 14
DUI 3(7.1,13.6) 18(3.6,81.8) 0(0,0) 1(0.9,4.5) 22
Fatigue 6(14.3,9) 54(10.9,80.6) 1(16.7,1.5) 6(5.2,9) 67
Brake defect 0(0,0) 14(2.8,77.8) 0(0,0) 4(3.5,22.2) 18
Overloading 0(0,0) 8(1.6,72.7) 0(0,0) 3(2.6,27.3) 11
Risky driving 5(11.9,4.4) 91(18.3,80.5) 1(16.7,0.9) 16(13.9,14.2) 113
Road defect 5(11.9,13.9) 17(3.4,47.2) 0(0,0) 14(12.2,38.9) 36
SHE 5(11.9,14.7) 25(5,73.5) 2(33.3,5.9) 2(1.7,5.9) 34
Speeding 3(7.1,3.3) 68(13.7,74.7) 1(16.7,1.1) 19(16.5,20.9) 91
Tyre defect 1(2.4,7.1) 9(1.8,64.3) 0(0,0) 4(3.5,28.6) 14
Total 42 497 6 115 660
Table 32 Injury and crash occurrence factors by weather condition
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For crash occurrence, all factors are significant for crashes occurring on fine days compared to other weather conditions. Nevertheless, an increase in the number of crashes related to road defect (38.9%), tyre defect (28.6%), overloading (27.3%), brake defect (22.2%), speeding (20.9%) and risky driving (14.2%) is observed during rainy days.
4.14 Lighting Condition
Table 33 indicates injury and crash occurrence factors according to lighting condition during the crashes. The highest number of cases (317 or 46.7%) is recorded during daylight, in which risky driving is the highest contributing factor (19.2%).
Factors Dark with lighting
Dark without lighting
Dawn/dusk Daylight Total
Injury Count (% by column, % by row)Crash compatibility 5(5.7,5.7) 27(12.9,31) 12(18.5,13.8) 43(13.6,49.4) 87
Mech. defect/Other 3(3.4,10.7) 10(4.8,35.7) 2(3.1,7.1) 13(4.1,46.4) 28
Use of restraint device
9(10.3,15.3) 16(7.6,27.1) 5(7.7,8.5) 29(9.1,49.2) 59
Roadside hazard 3(3.4,9.4) 8(3.8,25) 3(4.6,9.4) 18(5.7,56.3) 32
Structure integrity 3(3.4,18.8) 4(1.9,25) 2(3.1,12.5) 7(2.2,43.8) 16
Substandard crash barrier
2(2.3,12.5) 6(2.9,37.5) 2(3.1,12.5) 6(1.9,37.5) 16
Superstructure 2(2.3,40) 1(0.5,20) 1(1.5,20) 1(0.3,20) 5
Seat anchorage 1(1.1,33.3) 2(1,66.7) 0(0,0) 0(0,0) 3
Crash Count (% by column, % by row)Conspicuousness 2(2.3,14.3) 4(1.9,28.6) 1(1.5,7.1) 7(2.2,50) 14
DUI 6(6.9,27.3) 11(5.2,50) 1(1.5,4.5) 4(1.3,18.2) 22
Fatigue 12(13.8,17.4) 27(12.9,39.1) 5(7.7,7.2) 25(7.9,36.2) 69
Brake defect 1(1.1,5.3) 6(2.9,31.6) 1(1.5,5.3) 11(3.5,57.9) 19
Overloading 0(0,0) 3(1.4,27.3) 1(1.5,9.1) 7(2.2,63.6) 11
Risky driving 18(20.7,15.4) 28(13.3,23.9) 10(15.4,8.5) 61(19.2,52.1) 117
Road defect 4(4.6,11.1) 9(4.3,25) 4(6.2,11.1) 19(6,52.8) 36
Crash Count (% by column, % by row)SHE 4(4.6,10.5) 15(7.1,39.5) 4(6.2,10.5) 15(4.7,39.5) 38
Speeding 11(12.6,11.8) 30(14.3,32.3) 11(16.9,11.8) 41(12.9,44.1) 93
Tyre defect 1(1.1,7.1) 3(1.4,21.4) 0(0,0) 10(3.2,71.4) 14
Total 87 210 65 317 679
Table 33 Injury and crash occurrence factors by lighting condition
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In the absence of sufficient natural lighting, crashes on roads without lighting facilities record the highest number of cases (210 cases or 30.9%). In addition, half of the crashes that occurred in dark conditions are due to driving under the influence (DUI). In view of the crashes during dawn/dusk, cases related to crash compatibility, speeding, and risky driving are recorded high, with 18.5%, 16.9% and 15.4%, respectively.
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5.0 Conclusion
For the past four years (2007 to 2010), MIROS has successfully investigated 439 road crashes which involved three fatalities and above for cases involving all types of vehicles and at least one fatality involving commercial vehicles. The number of investigated cases, however, did not reflect the actual situation of nationwide crash distribution pattern involving the same pre-determined criteria set by MIROS. This is influenced by the crash monitoring and notification system used which was mainly focusing on media monitoring portal and also the capacity of MIROS’ resources.
The findings provide in-depth information which are not available from the national road crash database. This valuable information will assist in the reconstruction processes in order to determine the dynamics and mechanics of the crash and the development and implementation of impactful intervention. Moreover, the findings are also useful to guide researchers and practitioners of road safety on the critical issues relating to serious crashes.
Crashes involving any types of vehicles with three fatalities and above and those specifically involving commercial vehicles with at least one fatality contributed the highest proportion of investigated crashes throughout the four-year period. In terms of comparison between the two types of crash criteria, crashes with three fatalities and above have significantly lower frequency compared to crashes with less than three fatalities. From the total number of 439 investigated crashes, 47% are fatal accidents, 31% caused severely injured occupants and 22% caused minor injury to occupants.
From 2007 through 2010, head-on and hitting object collisions consistently record the most common types of crashes in terms of nationwide investigated cases. Passenger vehicles record the
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highest involvement in crashes with the pre-determined criteria mentioned in the previous paragraph for the four consecutive years. Johor, Pahang, Perak and Selangor are the states with the most prominent number of investigated crashes during the four-year period.
Crash compatibility, risky driving and speeding contribute to a significant number of fatalities. All crashes related to superstructure, seat anchorage failure, driving under the influence, brake defect and overloading record at least one fatality with none ‘injury only’ cases recorded. In other words, crashes related to the above factors tend to be more severe and ultimately cause higher number of fatalities.
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References
Nursitihazlin, AT (2006), The fatality index of public transport (express bus) in Malaysia, Serdang: Universiti Putra Malaysia.
REAM (1997), Guide on geometric design of road, Shah Alam: Road Engineering Association of Malaysia.
Road Transport Department of Malaysia (2010), Road Transport Act 1987 (ACT 333), Amendment Act 2010.
Royal Malaysian Police (RMP) (n.d.), Panduan mengisi borang polis 27 (pindaan 1/91).
Malaysian Institute of Road Safety ResearchLot 125-135, Jalan TKS 1, Taman Kajang Sentral43000 Kajang, Selangor Darul EhsanTel +603 8924 9200 Fax + 603 8733 2005Website www.miros.gov.my Email dg@miros.gov.my
Research Report
MIROS Crash Investigation and ReconstructionAnnual Statistical Report 2007–2010
Research Report
MIROS Crash Investigation and Reconstruction Annual Statistical Report 2007–2010
Ahmad Noor Syukri Zainal Abidin Siti Atiqah Mohd FaudziFauziana LaminAbdul Rahmat Abdul Manap
Designed by: Publications Unit, MIROS
MRR 05/2012
MRR_MIROS Crash Investigation and Reconstruction Annual Statistical Report 2007-2010_Syukri_28Jun12 (checked).indd 62 7/16/12 4:59 PM
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