Tracking the Evolution of Public Transport Demand using Spatial-Social-Temporal Contexts

Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation Pub Date : 2019-11-13 DOI:10.1145/3360322.3360870

R. Cardell-Oliver, Prathyusha Sangam

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Abstract

Changes in the way people live and move in cities is driving large investments in public transport infrastructure and services. Understanding long term evolution of demand is important for maximising the benefits of these investments. This short paper introduces an approach for highlighting changes in demand over time periods of several years. The main idea is to discover and explain distinctive contexts. The input data are trip logs from transport smart card tickets and a calendar feature database sourced from local web sources. Contexts comprise arrival counts over a set of days for a particular spatial region of the network and social type of traveller. Prose and visual representations of context pairs are used to explain how demand has evolved. Ground truth data of real-world events sourced from online reports is used to demonstrate that our approach accurately highlights and gives plausible explanations for changes in public transport demand.

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基于时空背景的公共交通需求演变跟踪研究

人们在城市生活和移动方式的改变，推动了对公共交通基础设施和服务的大量投资。了解需求的长期演变对于最大化这些投资的收益非常重要。这篇短文介绍了一种方法来突出几年时间内需求的变化。主要思想是发现和解释独特的语境。输入数据是来自交通智能卡门票的旅行日志和来自本地网络资源的日历特征数据库。背景包括在网络的特定空间区域和旅行者的社会类型的一组天的到达计数。使用散文和上下文对的可视化表示来解释需求是如何演变的。来自在线报告的真实世界事件的真实数据被用来证明我们的方法准确地突出了公共交通需求的变化，并给出了合理的解释。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

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