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In this paper we focus on the estimation of crowding in public transport – specifically urban rail systems – and its effect on perceived comfort. It is different from similar studies in the method it employs for estimating crowding levels in vehicles. Specifically, we formulate a function of time and location, which uses only passenger embarking data to estimate the number of passengers in vehicles. Then we convert the estimated crowding values into perceived discomfort levels by trip section. Our method depends on hourly seasonality assumptions but provides good estimates of crowding in urban rail systems even when passenger alighting data is not available. We illustrate the implementation of our model with the example of the Istanbul Metro system.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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