Use of Data Mining Technique for Systematic Road Safety Audit of Non-urban Highways
Bincy B.J1, Anitha Jacob2
1Bincy B.J, Department of Civil Engineering, Jyothi Engineering College, Cheruthuruthy, Thrissur (Kerala), India.
2Dr. Anitha Jacob, Department of Civil Engineering, Jyothi Engineering College, Cheruthuruthy, Thrissur (Kerala), India.
Manuscript received on 05 December 2018 | Revised Manuscript received on 19 December 2018 | Manuscript published on 30 December 2018 | PP: 92-96 | Volume-8 Issue-2C, December 2018 | Retrieval Number: 100.1/ijeat.ICID-2018_TE_210
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In India the number of road crashes is raising at frightening rate. There is one death in every four minutes due to road crashes in India. Hence it is necessary to improve the road safety by conducting a detailed Road Safety Audit (RSA) in order to identify road safety issues and to make necessary improvements. Budgetary constraints limit many developing countries from performing the audit on regular basis. This will eventually delay any rehabilitation or repair process making the road conditions the worst and risky. This paper proposes a systematic approach to do the road safety audit on a highway and to do effective and efficient data mining, for deriving knowledge driven decisions in the classification of highway sections. The approach will help to perform safety evaluation of sections and to identify the crash potential locations. Further output of the work is the development of a mathematical model for classification of highway sections based on road safety audit.
Keywords: Data Mining, Weka, Road Safety Audit, Road Safety Model.
Scope of the Article: Highways