Offline framework for the diagnosis of transfer reliability by Automatic Vehicle Location Data

In public transit networks, transfers occur when more than one route is used to connect origins and destinations. Much research has been done to investigate the design and management of transfers at the tactical and operational levels. However, very few studies have investigated the monitoring phase to check a posteriori if transfers are well planned and/or delivered according to archived automatic vehicle location (AVL) data. This article covers this gap by proposing the first offline framework. This framework preprocesses AVL raw data, performs a diagnosis of transfer reliability over all bus stops and time periods, and discloses the most common sources of transfer unreliability. Easy-to-read control dashboards show the viability of this framework on real bus routes with approximately 145,000 AVL data records to make an accurate transfer analysis and possible service adjustments.