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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

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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


iii

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

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iv

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


v

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

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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


vii

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

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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


ix

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)


x

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


xi

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


xiii

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.


xv

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


1

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


2

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.


3

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


4

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).


5

Figure 3 Investigated cases by day of occurrence, 2007

Num

ber o

f cas

es

Day


Num

ber o

f cas

es

Day

Num

ber o

f cas

es

Day

Monday

Tuesd

ay

Wednesday

Thursday

Friday

Saturday

Sunday



6

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


Num

ber o

f cas

es

Time

Figure 7 Investigated cases by time of occurrence, 2007


7

Num

ber o

f cas

es

Time


Num

ber o

f cas

es

Time


Num

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f cas

es

Time



8

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

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es

Month


9

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es

Month


Num

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es

Month


Num

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Month



10

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

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es

State



11

Num

ber o

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es

State


Num

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es

State



12

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


13




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


14




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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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


16

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



17

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


Num

ber o

f cas

es

Crash type



18

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

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f veh

icle

s

Vehicle type



19

Num

ber o

f veh

icle

s

Vehicle type



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.


20

Num

ber o

f cas

es

Vehicle involved

Figure 27 Investigated cases by number of vehicles involved, 2007


Num

ber o

f cas

es

Vehicle involved

Num

ber o

f cas

es

Vehicle involved



21

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).


Num

ber o

f cas

es

Vehicle involved

Figure 31 Investigated cases by road type, 2007

Num

ber o

f cas

es

Road type


22

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).


Num

ber o

f cas

es

Road type

Num

ber o

f cas

es

Road type



23

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 35 Investigated cases by intersection type, 2007

Intersection

Num

ber o

f cas

es


24

Intersection

Num

ber o

f cas

es



Intersection

Num

ber o

f cas

es

Intersection

Num

ber o

f cas

es



25

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

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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%).


26

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


27

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


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


28

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.


Vici

nity

Number of cases


Vici

nity

Number of cases


29

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


30

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


31

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


32

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



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


33

Table 7 Fatality and KSI indexes by month



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.


34

Table 8 Fatality and KSI indexes by state



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


35

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



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


36

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



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.


37

Table 11 Fatality and KSI indexes by intersection type



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



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.


38

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.



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



Index

Flat 265 Fatal 632 2.38

KSI 1075 4.06

Slope 117 Fatal 374 3.20

KSI 609 5.25


39

Table 15 Fatality and KSI indexes by number of vehicles involved



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


40

Table 18 Fatality and KSI indexes by weather condition



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



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).


41

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



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


42

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.


43

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

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13.6

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(18.

8,13

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9.1,

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34

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def

ect

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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


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


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


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


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


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


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%).


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

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0,0)

15(9

,25.

9)0(

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3(3.

6,5.

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2.2,

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0(0,

0)13

(14.

1,22

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1(8.

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7)58

Road

side

haz

ard

0(0,

0)1(

50,2

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25(1

5,73

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2.4,

5.9)

4(4.

4,11

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0(0,

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5.9)

0(0,

0)34

Stru

ctur

e in

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ity7(

3.3,

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1(1.

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0,0)

17

Subs

tand

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Supe

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0.5,

20)

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Seat

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0(0,

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0.6,

33.3

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)0(

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1(1.

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0(0,

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Cras

h Co

unt (

% b

y co

lum

n, %

by

row

)

Cons

picu

ousn

ess

3(1.

4,18

.8)

0(0,

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16.7

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ue15

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4)0(

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1(8.

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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


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


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


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


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


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


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%).


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


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


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


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


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.


50

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


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


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


51

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


52

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.


53

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


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


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.


54

Factors Single Dual Total


Crash compatibility 49(12.9,55.1) 40(13,44.9) 89


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


Superstructure 2(0.5,40) 3(1,60) 5

Seat anchorage 1(0.3,33.3) 2(0.6,66.7) 3


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


55

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


56

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


57

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


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


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


58

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.


59

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


60

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.


61

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 [email protected]

Research Report


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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