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New technologies such as automatic vehicle location (AVL) and automatic passenger counters (APC) make tremendous amounts of data available to transit planners and operators. Transit agencies would like to use these data to inform service planning and management and ultimately to provide more reliable service. This requires data processing in such a way as to provide pertinent information to transit planners. The research presented considers a sample of data collected from Chicago Transit Authority buses during the initial stage of AVL and APC implementation in Chicago, Illinois. Methods were developed for extracting information from these data that could be used to compute service reliability indicators. This research also discusses some of the challenges encountered in the data collection process. At the time of the data collection, the home garage for the bus route under consideration was not fully stocked with AVL-equipped buses. Other challenges included the misplacement of some time points and undercounting by the APC system. The data proved useful even with these challenges, and valuable information, such as bus travel patterns, schedule adherence, and headway regularity, was gained from this study. By recognizing some of the challenges faced in the data collection process, this research provided insights that can be used to inform future larger-scale studies of transit operations using AVL and APC data.

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