This paper presents a stop-level simulation framework for measuring transit line reliability using AVL and APC data. The framework quantifies reliability from the passenger perspective by estimating expected waiting times under observed headway irregularity and crowding conditions. For each stop, AVL data provide vehicle arrival times and APC data supply boarding and alighting counts, enabling a microsimulation of passenger arrivals, queue formation, and capacity-constrained boarding. The resulting waiting times yield a stop-level reliability index that reflects both headway variability and the effective loss of capacity due to crowding.

The framework is demonstrated using a TTC bus stop on Line 29, with simulations performed for multiple time periods and benchmarked against fully regular, Erlang-2, and exponential headway distributions. Results show that the observed headway pattern exhibits moderately irregular behavior, lying between the Erlang-2 and exponential benchmarks. The study also describes how the estimated reliability parameters can be incorporated into transit assignment models through a crowding-dependent effective headway formulation. The full paper will extend the analysis to the entire TTC network and evaluate the impacts of reliability-adjusted headways on regional transit assignment outcomes.