Grab-Posisi

Abstract

Real-world GPS trajectory datasets are essential for geographical applications such as map inference, map matching, traffic detection, etc. Currently only a handful of GPS trajectory datasets are publicly available and the quality of these datasets varies. Most of the existing datasets have limited geographical coverage (a focus on China or the USA), have low sampling rates and less contextual information of the GPS pings. This paper presents Grab-Posisi, the first GPS trajectory dataset of Southeast Asia from both developed countries (Singapore) and developing countries (Jakarta, Indonesia). The data were collected very recently in April 2019 with a 1 second sampling rate, which is the highest amongst all the existing open source datasets. It also has richer contextual information, including the accuracy level, bearing, speed and labels trajectories by data acquisition source (Android or iOS phones) and driving mode (Car or Motorcycle). The dataset contains more than 88 million pings and covers more than 1 million kms. Experiments on the dataset demonstrate new challenges for various geographical applications. The dataset is of great value and a significant resource for the community to benchmark and revisit existing algorithms.