An Importance Segregation Based Multi-Objective Optimization Model for Traffic Safety Improvement Countermeasure Selection

• Main Authors: Jie Yu, Yue Liu, Jing Mao
• Format: Article
• Language: English
• Published: Elsevier 2012-06-01
• Series: International Journal of Transportation Science and Technology
• Subjects: Multi-objective decision making; Importance Segregation; Traffic safety; Countermeasure selection; Transportation engineering
• Online Access: http://www.sciencedirect.com/science/article/pii/S2046043016301587

This paper presents a multi-objective optimization model to decide effective and beneficial portfolio for implementing traffic safety improvements under budgetary constraints. Different from the conventional multi-objective approaches, the proposed model segregates decision criteria into different importance levels and designs a successive optimization approach to obtain the final solution(s). Such modeling features offer the advantages to: 1) prevent the arbitrariness for transportation agencies to determine weights for decision criteria; 2) remedy the deficiency of over-weighting less important criteria in the traditional multi-objective optimization approach; and 3) minimize the number of potential solutions for final decision by transportation agencies with enhanced screening of the sub-optimal solutions. Case study results reveal that the proposed model is efficient not only for deciding the most suitable traffic safety countermeasure for a specific site, but also for determining the plans for implementing multiple countermeasures among multiple sites given the budget constraint. Comparative study results have also indicated that the proposed model outperforms the traditional criteria in objectively selecting traffic safety improvements in a multi-criteria decision-making process. The clarity of model inputs and the interpretation of results with respect to different selection criteria offer its best potential to be used as an effective decision-support tool for transportation authorities to assess and refine their safety improvement investments.