Bus Fleet Type and Age Replacement Optimization: A case study utilizing King County Metro fleet data

Abstract

Bus fleet data have consistently shown that vehicle operating and maintenance costs increase as vehicles age. A fleet manager has to deal with the tradeoff between the lower operating and maintenance costs of newer fleets and their higher initial capital costs as well as the tradeoff between conventional and fuel efficient bus technologies. This study formulates and implements a fleet replacement optimization framework that is applied to a case study that compares two bus types: a conventional diesel and a hybrid bus. Employing real-world bus fleet data from King County Metro (Washington State, USA) multiple scenarios are examined to account for uncertainty and variability in the model parameters. In addition sensitivity analyses are performed to study the impacts of parameter values on optimal replacement policies and the per-mile costs. Key findings include: the Federal Transit Administration (FTA) purchase cost subsidy has the highest impact on the optimal replacement policies; without FTA subsidy it is always cost effective to adopt diesel buses and replace them every 20 years. With an 80% purchase cost FTA subsidy, hybrid buses are the best choice; the optimal hybrid bus replacement cycle decreases from 18 to 14 years with increasing annual utilizations and operating and maintenance costs or decreasing hybrid purchase price and fuel economy. Fuel price, emissions costs, and initial bus age have little impact on optimal replacement policies. However, discount rate and diesel bus price, annual utilization (in 0% FTA subsidy scenario) and fuel price (in 80% FTA subsidy scenario) have the highest impacts on per-mile costs.

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