Abstract Despite the efforts placed by major European cities to optimize public transportation, traffic data analytics often disregard vital situational context. This work proposes a methodology to integrate situational context (including public events, planned interventions and citizen notifications) in the analysis of public transport data. The major contributions are the: online consolidation and labeling of heterogeneous sources of context; calendar-driven statistical modeling of expected traffic behavior; and the integrative display of traffic and its situational context, accompanied by spatiotemporal navigation and zooming facilities. Preliminary results collected from the Lisbon's subway network system shows the relevance of these contributions to support context-sensitive decisions.
Leite et al. (Wed,) studied this question.
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