Simulation Based-MCDM Approach for Evaluating Traffic Solutions

Traffic congestion problems have dramatically esca-lated with the increasing volume of vehicles, pedestrians, and cyclists in the face of limited road capacity. This re-search aims to reduce the time road users spend in the system (school-zone area) and improve the efficiency of the process of dropping off and collecting children from a crowded school area. The study integrates discrete-event simulation (DES) and multi-criterion decision-mak-ing (MCDM) techniques to comprehensively evaluate the proposed alternatives to select an optimal solution based on many performance measures. A real-world case study of the traffic and congestion problems experienced by parents when they drop off and fetch their children from school during peak hours is presented. A heuristic algorithm was developed to simulate the random and un-predictable behaviour of road users. A cost-benefit anal-ysis considered the impact of waiting time, traffic den-sity, number of accidents, additional fuel expenses, and emission reduction. The technique for order of preference by similarity to ideal solution (TOPSIS) and preference selection index (PSI) methods were utilised to select the most appropriate option for parents. The study found that the integration of simulation techniques with MCDM methods could efficiently solve traffic problems.