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    1. Bus

    CA: Improved Model Helps Transit Agencies Predict More Accurate Staffing for Bus Routes

    July 31, 2015
    The Mineta National Transit Research Consortium’s latest peer-reviewed study, Understanding and Modeling Bus Transit Driver Availability, has tested three models and provided a series of recommendations to help transit agencies plan for a sufficient number of drivers without over-scheduling.
    Related To: Mineta Transportation Institute (MTI)

    The Mineta National Transit Research Consortium’s latest peer-reviewed study, Understanding and Modeling Bus Transit Driver Availability, has tested three models and provided a series of recommendations to help transit agencies plan for a sufficient number of drivers without over-scheduling. Principal investigator was Kaan Ozbay, PhD, working with Ender Faruk Morgul, MSc. The report is available at http://transweb.sjsu.edu/project/1140.html

    To accommodate unplanned employee absences (illness, emergencies, etc.), transit agencies must employ a sufficient number of transit vehicle operators to meet the demands of scheduled service. Therefore, agencies employ extraboard operators, or on-call backups. Overestimating the number of extraboard operators can be costly, and underestimating can cause service problems. This study proposes stochastic (i.e., random or probability) mathematical models so transit agencies can predict necessary staffing more accurately.

    “Currently, decision makers estimate their staffing by using personal experience and intuition,” said Dr. Ozbay. “However, our mathematical models account for measures of risk and reliability with probability distributions based on historical data. Implementing these models could allow agencies to realize meaningful cost reductions while maintaining proper staffing.”

    The proposed models could also improve policies for daily transit operations, allowing agencies to better determine the minimum extra driver run hours for different levels of reliability while better understanding the relationship between social costs and operational costs. Social costs are defined using clearly identified measures estimated for the case study area, such as the value of riding per hour and the average number of passengers.

    Implementing these models in a user-friendly computer tool could lead to other improvements by creating various scenarios to increase the speed and efficiency of decision-making. The demand and supply data required for the model validation was obtained from historical data of the Tri-County Metropolitan Transportation District of Oregon (TriMet).

    As seen in several US and European studies, average absenteeism among bus drivers is considerably higher than in other industry groups. In one US-based study, researchers found that an average transit operator misses approximately 12 percent of annual scheduled workdays, excluding vacations and holidays. Other studies have noted that absenteeism places a significant economic burden on an overall transportation budget.

    In this study the researchers consider the tactical planning problem, in which extra workforce numbers are determined daily, depending on schedule requirements and garage assignments.

    The report’s figures and tables include a TriMet daily extraboard profile, stochastic model graphs, garage location map, model results for cost scenarios and more.