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Evaluating the systemic effects of automated mobility-on-demand services via large-scale agent-based simulation of auto-dependent prototype cities
Transportation Research Part A: Policy and Practice ( IF 6.3 ) Pub Date : 2020-08-28 , DOI: 10.1016/j.tra.2020.06.013
Jimi B. Oke , Arun Prakash Akkinepally , Siyu Chen , Yifei Xie , Youssef M. Aboutaleb , Carlos Lima Azevedo , P. Christopher Zegras , Joseph Ferreira , Moshe Ben-Akiva

The growing demand for urban mobility highlights the need for relevant and sustainable solutions in cities worldwide. Thus, we develop and implement a framework to analyze the systemic impacts of future urban mobility trends and policies. We build on prior work in classifying the world’s cities into 12 urban typologies that represent distinct land-use and behavioral characteristics by introducing a generalized approach for creating a detailed, simulatable prototype city that is representative of a given typology. We then generate and simulate two auto-dependent (largely US-specific) prototype cities via a state-of-the-art agent-based platform, SimMobility, for integrated demand microsimulation and supply mesoscopic simulation. We demonstrate the framework by analyzing the impacts of automated mobility on-demand (AMoD) implementation strategies in the cities based on demand, congestion, energy consumption and emissions outcomes. Our results show that the introduction of AMoD cannibalizes mass transit while increasing vehicle kilometers traveled (VKT) and congestion. In sprawling auto-dependent cities with low transit penetration, the congestion and energy consumption effects under best-case assumptions are similar regardless of whether AMoD competes with or complements mass transit. In dense auto-dependent cities with moderate transit modeshare, the integration of AMoD with transit yields better outcomes in terms of VKT and congestion. Such cities cannot afford to disinvest in mass transit, as this would result in unsustainable outcomes. Overall, this framework can provide insights into how AMoD can be sustainably harnessed not only in low-density and high-density auto-dependent cities, but also in other typologies.



中文翻译:

通过基于代理的自动依赖原型城市的大规模模拟评估自动化按需移动服务的系统效果

对城市交通的需求不断增长,突显了全球城市需要相关且可持续的解决方案的需求。因此,我们开发并实施了一个框架来分析未来城市交通趋势和政策的系统性影响。我们在先前的工作基础上,通过引入通用方法来创建代表特定类型的详细,可模拟的原型城市,将世界城市分为代表不同土地用途和行为特征的12种城市类型。然后,我们通过基于代理的最新平台SimMobility生成并模拟两个自动相关(主要在美国特定)的原型城市,以进行综合需求微观模拟和供应介观模拟。我们通过根据需求,交通拥堵,能源消耗和排放结果分析城市自动驾驶按需(AMoD)实施策略的影响来演示该框架。我们的结果表明,引入AMoD可以吞噬公共交通,同时增加车辆行驶的公里数(VKT)和交通拥堵。在交通依赖程度低的庞大的依赖汽车的城市中,无论AMoD是否与大众运输竞争还是互补,在最佳情况下的拥堵和能源消耗效应都是相似的。在交通模式份额适中的人口密集型自动依赖城市中,AMoD与交通方式的集成在VKT和交通拥堵方面产生了更好的结果。这些城市无力对公共交通进行投资,因为这将导致不可持续的结果。总体,

更新日期:2020-08-29
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