Current transit suffers from an evident inequity: the level of service of transit in suburbs is much less satisfying than in city centers. As a consequence, private cars are still the dominant transportation mode for suburban people, which results in congestion and pollution. To achieve sustainability goals and reduce car-dependency, transit should be (re)designed around equity. To this aim, it is necessary to (i) quantify the "level of equity" of the transit system and (ii) provide an indicator that scores the transit lines that contribute the most to keep transit equitable. This indicator could suggest on which lines the transit operator must invest to increase the service level (frequency or coverage) in order to reduce inequity in the system. To the best of our knowledge, this paper is the first to tackle (ii). To this aim, we propose efficient scoring methods that rely solely on open data, which allows us to perform the analysis on multiple cities (7 in this paper). Our method can be used to guide large-scale iterative optimization algorithms to improve accessibility equity.
翻译:目前过境明显不公平:郊区的过境服务水平远不如城市中心满意,因此,私人汽车仍然是郊区居民的主要运输方式,造成拥挤和污染。为了实现可持续性目标和减少汽车依赖,过境应该(重新)围绕公平问题进行设计。为此,必须(一) 量化过境系统的“公平程度”和(二) 提供指数,分数最有助于保持过境公平的过境路线。这个指标可以表明过境运营商必须投资哪条路线来增加服务水平(频率或覆盖面),以减少系统的不平等。根据我们的知识,本文件是第一个解决(二) 的目标。我们建议只依靠开放数据的有效评分方法,从而使我们能够对多个城市进行分析(本文中7个)。我们的方法可以用来指导大规模迭代最优化算法,以提高无障碍的公平性。