# Inferring Accurate Bus Trajectories from Noisy Estimated Arrival Time Records

## TL;DR

This paper presents a framework to infer precise bus trajectories from noisy ETA data, enabling better urban mobility analysis without relying on private transaction records.

## Contribution

The study introduces a novel method to reconstruct accurate bus trajectories from publicly available noisy ETA data, validated in Singapore and London.

## Key findings

- Achieved high-accuracy trajectory reconstruction from noisy ETA records
- Quantified the spatiotemporal resolution limits of the reconstructed trajectories
- Validated the approach across two major cities

## Abstract

Urban commuting data has long been a vital source of understanding population mobility behaviour and has been widely adopted for various applications such as transport infrastructure planning and urban anomaly detection. While individual-specific transaction records (such as smart card (tap-in, tap-out) data or taxi trip records) hold a wealth of information, these are often private data available only to the service provider (e.g., taxicab operator). In this work, we explore the utility in harnessing publicly available, albeit noisy, transportation datasets, such as noisy "Estimated Time of Arrival" (ETA) records (commonly available to commuters through transit Apps or electronic signages). We first propose a framework to extract accurate individual bus trajectories from such ETA records, and present results from both a primary city (Singapore) and a secondary city (London) to validate the techniques. Finally, we quantify the upper bound on the spatiotemporal resolution, of the reconstructed trajectory outputs, achieved by our proposed technique.