Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ssci.2011.05.001
Title: A Genetic algorithm approach to assessing work zone casualty risk
Authors: Meng, Q. 
Weng, J.
Keywords: Casualty risk
Classification rule
Crash
Genetic algorithm
Work zone
Issue Date: Oct-2011
Source: Meng, Q., Weng, J. (2011-10). A Genetic algorithm approach to assessing work zone casualty risk. Safety Science 49 (8-9) : 1283-1288. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ssci.2011.05.001
Abstract: This paper proposes a genetic algorithm (GA) approach to assessing work zone casualty risk defined as the likelihood of a vehicle occupant being killed or injured in a work zone crash. The proposed GA approach consists of three components: chromosome coding, fitness function and genetic operators. Based on the Michigan M-94{minus 45 degree rule}I-94{minus 45 degree rule}I-94BL{minus 45 degree rule}I-94BR highway work zone crash data, 19 classification rules are identified using the proposed GA approach to determine the work zone casualty risk. The results show that the variable of seat position has the most significant effect on reducing the prediction error of the GA approach. The variables of posted speed limit, traffic control devices and truck or bus involved are found to have no effects on improving the prediction performance. The GA approach outperforms the binary logistic regression technique in terms of the prediction accuracy. This demonstrates that the GA approach is a good alternative for the work zone casualty risk assessment. © 2011 Elsevier Ltd.
Source Title: Safety Science
URI: http://scholarbank.nus.edu.sg/handle/10635/54211
ISSN: 09257535
DOI: 10.1016/j.ssci.2011.05.001
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