Development of a safety performance function for motorcycle accident fatalities on Malaysian primary roads

Manan, Muhammad Marizwan Abdul; Jonsson, Thomas; Várhelyi, András

doi:10.1016/j.ssci.2013.06.005

Cited by 61 publications

(27 citation statements)

References 23 publications

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“…Due to time limitation or lack of interest, all the details are not recorded by them and Malaysia is no exception. Discrepancy in Malaysian accident data has been highlighted in previous research [2]. Other low and middle-income or developing countries also experience similar problems related to their accident data such as China [3], South Africa [4] and Saudi Arabia [5].…”

Section: Introductionmentioning

confidence: 72%

The Effect of Type of Attributes on the Fill-Ability of Accident Reporting Forms (ARF)

Ahmed¹,

Ahmad²,

Sadullah³

et al. 2020

(JTTM)

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Accident Reporting Form (ARF) is the basic building block of an Accident Database. Incorrect and incomplete forms result into the formation of erroneous database which contains partial or no essential information required for the statistical analysis of accident data. Policies made on the basis of the results of such databases will have little or no effect on the improvement of safety of roadway facilities. In most countries filling of the ARF is the responsibility of Police/Investigating officers. Due to lack of interest, all the details are not recorded by them. Thus, it is very important to investigate the type of attributes and their respective items filled most. The objective of this study is to evaluate the attributes given most importance by the person in charge of filling the ARF and the items most neglected. The probable reasons for the complete/incomplete recording of the details of certain items were also examined. For this study a total of 642 forms were obtained from the Malaysian Institute of Road Safety Research (MIROS) for evaluation. Each form contained 91 attributes, as per number given in the accident reporting form known as POL 27. The items were divided with respect to driver, passenger, vehicle, pedestrian, location, road environment, road information and additional information. The fill-ability for each item was estimated in terms of percent filled. The items were evaluated in terms of least and most filled and the probable reason for the complete/incomplete filling of each item was then investigated. It was found that items related to location were most neglected. The second most incomplete items were associated with the vehicle and the driver. While the attributes related to the road and the environment were found to be the most filled. The probable reason for lack of fill-ability of location related items was their placement in inappropriate sections. The important finding of this study is the high number of items in the POL 27 which makes it difficult for the officer to fill the form completely and is the major cause of reduced fill-ability.

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Section: Introductionmentioning

confidence: 72%

The Effect of Type of Attributes on the Fill-Ability of Accident Reporting Forms (ARF)

Ahmed¹,

Ahmad²,

Sadullah³

et al. 2020

(JTTM)

View full text Add to dashboard Cite

show abstract

“…Various research works have been developed to examine the trend of road accidents but only few studies have been conducted for Malaysia road accidents. Such studies can be found in [6,[12][13][14][15][16][17]. However the study which is focus on comparison of the different region or state is very limited.…”

Section: Related Studiesmentioning

confidence: 99%

Behavior of road accidents: Structural time series approach

Junus

Ismail

Arsad

2014

AIP Conference Proceedings

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Road accidents become a major issue in contributing to the increasing number of deaths. Few researchers suggest that road accidents occur due to road structure and road condition. The road structure and condition may differ according to the area and volume of traffic of the location. Therefore, this paper attempts to look up the behavior of the road accidents in four main regions in Peninsular Malaysia by employing a structural time series (STS) approach. STS offers the possibility of modelling the unobserved component such as trends and seasonal component and it is allowed to vary over time. The results found that the number of road accidents is described by a different model. Perhaps, the results imply that the government, especially a policy maker should consider to implement a different approach in ways to overcome the increasing number of road accidents.

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“…For instance, the number of fatal or injury collisions can be estimated by separating the estimated total crash frequencies as distributions of crash severity calibrated by local data. SPFs directly calibrated by fatal and injury (FI) collisions [11,12] or fatal collisions [13] have also been developed in previous studies. Although such procedures can be used to estimate the expected number of fatal collisions in sites that are segmented by roadway attributes, the infrequency of fatal collisions causes a bias in safety measures, such as the potential for safety improvement (PSI), due to the extremely low number of expected and observed values.…”

Section: Introductionmentioning

confidence: 99%

Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway

et al. 2021

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Detecting high-collision-concentration locations based solely on collision frequency may produce different results compared to those considering the severities of the collisions. In particular, it can lead government agencies focusing sites with a high collision frequency while neglecting those with a lower collision frequency but a higher percentage of injury and fatal collisions. This study developed systematic ways of detecting reproducible fatal collision locations (R) using the naïve Bayes approach and a continuous risk profile (CRP) that estimates the true collision risk by filtering out random noise in the data. The posterior probability of fatal collisions being reproducible at a location is estimated by the relationship between the spatial distribution of fatal-collision locations (i.e., likelihood) and the CRP (i.e., prior probability). The proposed method can be used to detect sites with the highest proxy measure of the posterior probability (PMP) of observing R. An empirical evaluation using 5-year traffic collision data from six routes in California shows that detecting R based on the PMP outperform those based on the SPF-based approaches or random selection, regardless of various conditions and parameters of the proposed method. This method only requires traffic collision and annual traffic volume data to estimate PMP that prioritize sites being R and the PMPs can be compared across multiple routes. Therefore, it helps government agencies prioritizing sites of multiple routes where the number of fatal collisions can be reduced, thus help them to save lives with limited resources of data collection.

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Development of a safety performance function for motorcycle accident fatalities on Malaysian primary roads

Cited by 61 publications

References 23 publications

The Effect of Type of Attributes on the Fill-Ability of Accident Reporting Forms (ARF)

The Effect of Type of Attributes on the Fill-Ability of Accident Reporting Forms (ARF)

Behavior of road accidents: Structural time series approach

Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway

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