Insights about service improvement in a transit network can be gained by studying transit service reliability. In this paper, a general procedure for constructing a transit service reliability diagnostic (Tsrd) diagram based on a Bayesian network is proposed to automatically build a behavioural model from Automatic Vehicle Location (AVL) and Automatic Passenger Counters (APC) data. Our purpose is to discover the variability of transit service attributes and their effects on traveller behaviour. A Tsrd diagram describes and helps to analyse factors affecting public transport by combining domain knowledge with statistical data.
|Title of host publication||Foundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Roskilde, Denmark, June 25-27, 2014. Proceedings|
|Number of pages||7|
|Publication status||Published - 2014|
|Series||Lecture Notes in Computer Science|