Abstract
The average amount of waiting time spent by commuters is one of the key indicators of service quality for public bus operations. While actual measurements of actual waiting time is difficult to be done en masse, models of waiting time can be derived from bus headways and these models have been adopted by transport planners in monitoring and regulating service reliability of operators. However, these models are founded on several assumptions on the patterns of commuter arrival which may not be applicable for bus services that experience high demand and heavily fluctuating commuter patterns. Given the availability of granular data on commuter boarding from automated fare collection systems, we propose a new methodology to better estimate the average waiting time of commuters. The formulation is anchored and validated using a three-month dataset from ten selected bus routes in Singapore. Finally, we discuss how our new measure allows for minimization of commuter waiting time through schedule optimization.
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