Potential Application of Artificial Neural Network (ANN) Analysis Method on Malaysian Road Crash Data

Authors

  • Ahmad Shahir Jamaludin Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pahang, Malaysia
  • Ahmad Noor Syukri Zainal Abidin Malaysian Institute of Road Safety Research, Taman Kajang Sentral, 43200, Kajang, Selangor, Malaysia
  • Mohd Nizar Muhd Razali Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pahang, Malaysia
  • Azzuhana Roslan Malaysian Institute of Road Safety Research, Taman Kajang Sentral, 43200, Kajang, Selangor, Malaysia
  • Roziana Shahril Malaysian Institute of Road Safety Research, Taman Kajang Sentral, 43200, Kajang, Selangor, Malaysia
  • Zulhaidi Mohd Jawi Malaysian Institute of Road Safety Research, Taman Kajang Sentral, 43200, Kajang, Selangor, Malaysia
  • Khairil Anwar Abu Kassim Malaysian Institute of Road Safety Research, Taman Kajang Sentral, 43200, Kajang, Selangor, Malaysia

DOI:

https://doi.org/10.15282/jmmst.v5i2.6706

Keywords:

Artificial Neural Network (ANN), Malaysia, Road Crash Data, Road Safety, Accident Investigation

Abstract

By allowing the movement of commodities and people, road transportation benefits both nations and people. This provides improved access to work opportunities, educational attainment, recreation, and healthcare, all of which have a direct and indirect influence on people. The influence on road transportation, on the other hand, has a detrimental impact on people's health. When addressing road traffic accidents, it is common known that it has merely become a global pandemic, with over a million people dying on the road each year. Malaysia, as a growing country, has identified road safety as a major issue that must be addressed. Reliable road safety statistics are critical for comprehending, assessing, and monitoring the nature and scope of the road safety problem and its solutions, for setting ambitious but realistic safety targets, for designing and implementing effective road safety policies, and for monitoring their success. Several approaches are presently utilized by road safety researchers to produce road safety indicators. In Malaysia, nearly all decisions made by the country's higher authorities to enhance road safety are based on data supplied by relevant stakeholders. As a result, having the proper application of analysis as well as the trustworthiness of the data itself is critical. This article will give a review of the possible use of the Artificial Neural Network (ANN) Analysis technique on traffic road collision data and what it may provide to assist monitor or forecast road safety issues, specifically in Malaysia. A new era in the field of road accident investigation is being ushered in by the development and application of analytical methodologies, which are creating previously unimaginable situations. Due to the convergence of recent advancements in accident research models and the availability of potentially new sources of traffic data, this paradigm shift has been made possible. The study of road crashes has benefited significantly from the development of more advanced data processing methodologies and frameworks, thus the researchers will able to extract significant conclusions from the study of traffic data thanks to the application of these approaches.

References

WHO, “Global Status Report on Road Safety 2013: Time for Action,” ISBN 978 92 4 156384 0, Geneva, World Health Organization

Rohayu, S., Sharifah Allyana, S.M.R., Jamilah, M.M. & Wong, S.V. (2012) Predicting Malaysian Road Fatalities for Year 2020. MRR 06/2012, MIROS, Kuala Lumpur.

Zulhaidi M. J., Khairil Anwar A. K., “3-5-2: How does NCAP for ASEAN Help the Region's Road Safety Index?”, Journal Society of Automotive Engineers Malaysia (JSAEM), 2013-007, Malaysian Institute of Road Safety Research (MIROS), 2013.

Press Release, Statistics on Causes of Death, Malaysia, Department of Statistics Malaysia (DOSM), 2020.

U. R. S. Radin, M. G. Mackay, and B. L. Hills, “Modelling of conspicuity-related motorcycle accidents in Seremban and Shah Alam, Malaysia,” Accident Analysis & Prevention, vol. 28, no. 3, pp. 325–332, 1996.

Mohamed Rehan, K (1995), A Macro Analysis of Road Accident Trends in Malaysia, Journal of Eastern Asia Society for Transportation Studies, 1(3):941-950.

G. Marsden and P. Bonsall, “Performance targets in transport policy,” Transport Policy, vol. 13, no. 3, pp. 191–203, 2006.

P. McCullagh and J. A. Nelder, “An outline of generalized linear models,” Generalized Linear Models, pp. 21–47, 1989.

M. Dougherty, “A review of neural networks applied to transport,” Transportation Research Part C: Emerging Technologies, vol. 3, no. 4, pp. 247–260, 1995.

Y.-C. Chiou, “An artificial neural network-based expert system for the appraisal of two-car crash accidents,” Accident Analysis & Prevention, vol. 38, no. 4, pp. 777–785, 2006.

S. A. Mohamed, K. Mohamed, and H. A. Al-Harthi., “Investigating Factors Affecting the Occurrence and Severity of Rear-End Crashes,” Transportation Research Procedia, vol. 25, pp. 2098–2107, 2017.

B. García de Soto, A. Bumbacher, M. Deublein, and B. T. Adey, “Predicting road traffic accidents using artificial neural network models,” Infrastructure Asset Management, vol. 5, no. 4, pp. 132–144, 2018.

M. M. Abdul Manan, A. Várhelyi, A. K. Çelik, and H. H. Hashim, “Road characteristics and environment factors associated with motorcycle fatal crashes in Malaysia,” IATSS Research, vol. 42, no. 4, pp. 207–220, 2018.

M. M. Abdul Manan and A. Várhelyi, “Motorcycle fatalities in Malaysia,” IATSS Research, vol. 36, no. 1, pp. 30–39, 2012.

M. M. Abdul Manan and A. Várhelyi, “Motorcyclists’ road safety related behavior at access points on primary roads in Malaysia – A case study,” Safety Science, vol. 77, pp. 80–94, 2015.

N. Che-Him, R. Roslan, M. S. Rusiman, K. Khalid, M. G. Kamardan, F. A. Arobi, and N. Mohamad, “Factors Affecting Road Traffic Accident in Batu Pahat, Johor, Malaysia,” Journal of Physics: Conference Series, vol. 995, p. 012033, 2018.

M. F. Musa, S. A. Hassan, and N. Mashros, “The impact of roadway conditions towards accident severity on federal roads in Malaysia,” PLOS ONE, vol. 15, no. 7, 2020.

M. Khairul Amri Kamarudin, N. Abd Wahab, R. Umar, A. Shakir Mohd Saudi, M. Hafiz Md Saad, N. Rozaireen Nik Rosdi1, Sarah Alisa Abdul Razak, M. Murtadha Merzuki, A. Salam Abdullah, S. Amirah, and A. Mohd Ridzuan, “Road Traffic Accident in Malaysia: Trends, Selected Underlying, Determinants and Status Intervention,” International Journal of Engineering & Technology, vol. 7, no. 4.34, p. 112, 2018.

M. J. Zulhaidi, M. I. Mohd Hafzi, S. Rohayu, S. Wong, M. S. Farhan, Weather as a road safety hazard in Malaysia — An overview. Malaysian Institute of Road Safety Research., 2010.

N. A. Kamaluddin, M. F. Abd Rahman, and A. Várhelyi, “Matching of police and hospital road crash casualty records – a data-linkage study in Malaysia,” International Journal of Injury Control and Safety Promotion, vol. 26, no. 1, pp. 52–59, 2018.

C.-Y. Ting, N. Y.-Z. Tan, H. H. Hashim, C. C. Ho, and A. Shabadin, “Malaysian Road Accident Severity: Variables and Predictive Models,” Lecture Notes in Electrical Engineering, pp. 699–708, 2020.

N. Samsuddin and M. I. Mohd Masirin, “Assessment of Road Infrastructures Pertaining to Malaysian Experience,” MATEC Web of Conferences, vol. 47, p. 03010, 2016.

J. Prasetijo, W. Z. Musa, Z. Mohd Jawi, Z. F. Zainal, N. B. Hamid, A. Subramaniyan, A. J. L. M. Siang, N. Anting, and I. Mohd Hafzi Md, “Vehicle Road Accident Prediction Model along Federal Road FT050 Kluang-A/Hitam-B/Pahat Route Using Excess Zero Data,” IOP Conference Series: Materials Science and Engineering, vol. 852, p. 012144, 2020.

N. Danlami, M. Napiah, A. F. M. Sadullah, N. Bala, “An Overview And Prediction Of Malaysian Road Fatality: Approach Using Generalized Estimating Equations,” International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 11, pp. 452–465, 2017

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Published

25-08-2021

How to Cite

Jamaludin, A. S., Zainal Abidin, A. N. S. ., Muhd Razali, M. N., Roslan, A., Shahril, R., Mohd Jawi, Z., & Abu Kassim, K. A. (2021). Potential Application of Artificial Neural Network (ANN) Analysis Method on Malaysian Road Crash Data. Journal of Modern Manufacturing Systems and Technology, 5(2), 95–105. https://doi.org/10.15282/jmmst.v5i2.6706

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