论文标题
迈向跨学科方法来解决新的（旧）运输问题
Toward An Interdisciplinary Methodology to Solve New (Old) Transportation Problems
论文作者
论文摘要
数字痕迹的可用性不断提高为城市中的新问题和旧问题提供了新的解决方案。即使用数据科学方法分析的大量数据集可能为问题提供了有力的解决方案，但由于采用阻碍者（例如缺乏可解释性和透明度），因此无法保证相关利益相关者的采用。在这种情况下，本文提出了一种初步方法，用于弥合两个学科，数据科学和运输，以使用适合采用的方法来解决城市问题。该方法由四个步骤定义，其中两个学科的人都从算法和模型定义转变为建立潜在的可采用解决方案。作为案例研究，我们描述了如何应用这种方法来定义模型以通过手机数据的运输方式推断通勤旅行。
The rising availability of digital traces provides a fertile ground for new solutions to both, new and old problems in cities. Even though a massive data set analyzed with Data Science methods may provide a powerful solution to a problem, its adoption by relevant stakeholders is not guaranteed, due to adoption blockers such as lack of interpretability and transparency. In this context, this paper proposes a preliminary methodology toward bridging two disciplines, Data Science and Transportation, to solve urban problems with methods that are suitable for adoption. The methodology is defined by four steps where people from both disciplines go from algorithm and model definition to the building of a potentially adoptable solution. As case study, we describe how this methodology was applied to define a model to infer commuting trips with mode of transportation from mobile phone data.
