Analyzing passenger density for public bus: Inference of crowdedness and evaluation of scheduling choices

Abstract

Bus service is an important public transportation. Besides the major goal of carrying passengers around, providing a comfortable travel experience for passengers is also an important business consideration. The crowdedness inside a bus can directly affect the number of people choosing the bus. Traditional approaches to obtain passenger density rely on field investigations, which are both non-scalable and incomplete. The wide adoptions of smart card fare collection systems and GPS tracing systems in public transportation provide new opportunities. In this paper, we associate these two independent datasets to derive the passenger density, and evaluate the effectiveness of scheduling choices. To our best knowledge, this is the first paper which utilizes smart card data and GPS data to calculate the passenger density of bus service.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 21 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.