调查聚合流动性指数的潜力,以推断公共交通乘客数量的变化
Maximiliano Lizana1,2, Charisma Choudhury1, David Watling1
1Institute for Transport Studies, University of Leeds, Leeds, United Kingdom.
PloS one
|January 5, 2024
概括
智能手机的聚合移动性指数 (AMI) 为追踪公共交通 (PT) 乘客提供了可靠的替代方案,尤其是在传统数据稀缺的情况下. 谷歌的移动性指数显示与实际PT需求有很强的对齐,表现优于果的移动性指数.
科学领域:
- 运输科学 运输科学
- 数据科学数据科学数据科学
- 城市规划 城市规划
背景情况:
- 来自信息和通信技术的汇总移动性指数 (AMI) 正在成为运输规划人员的有价值数据来源,特别是在中断或数据稀缺期间.
- 现有的AMI,来自于公共交通 (PT) 中枢中的智能手机GPS或PT导航查询,经常被用作PT需求的代理,但它们对实际乘客变化的可靠性基本上未经测试.
研究的目的:
- 严格比较AMI在推断公共交通乘客变化的可靠性与传统数据来源.
- 调查AMI与传统乘客数据的互补作用,特别是当售票数据受到损害时.
主要方法:
- 两个全球AMI (谷歌和果) 与全球12个城市的每月和每日乘客数据的比较.
- 分析侧重于2020-2022年间发生重大变化的时期.
- 探索AMI在补充智能卡验证和机票数据方面的实用性.
主要成果:
- 谷歌的移动性指数与乘客数量趋势显著一致,表现优于果的移动性指数.
- 与之前的研究相比,AMI的性能显著提高,这突显了解决数据集中的方法差异的重要性.
- 当售票信息缺失或不可靠时,AMI在补充智能卡数据方面被证明是有效的.
结论:
- 聚合的移动性指数,特别是那些基于人类移动模式的指数,为估计公共交通乘客变化提供了一种可靠的方法.
- AMI作为一种有价值的替代和补充数据源用于运输规划,特别是在传统数据有限的发展中国家.
- 对于准确比较不同移动数据源的方法论考虑至关重要.
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