In this chapter, we discuss urban mobility from a complexity science perspective. First, we give an overview of the datasets that enable this approach, such as mobile phone records, location-based social network traces, or GPS trajectories from sensors installed on vehicles. We then review the empirical and theoretical understanding of the properties of human movements, including the distribution of travel distances and times, the entropy of trajectories, and the interplay between exploration and exploitation of locations. Next, we explain generative and predictive models of individual mobility, and their limitations due to intrinsic limits of predictability. Finally, we discuss urban transport from a systemic perspective, including system-wide challenges like ridesharing, multimodality, and sustainable transport.
翻译:在本章中,我们从复杂的科学角度来讨论城市流动问题。首先,我们概要介绍促成这一方法的数据集,例如移动电话记录、基于地点的社会网络跟踪或从安装在车辆上的传感器上移动的全球定位系统轨迹。然后,我们从经验和理论上审查对人流动特性的认知,包括旅行距离和时间分布、轨迹的环状以及地点探索和开发之间的相互作用。接下来,我们解释个人流动的基因化和预测模型,以及由于内在的可预测性限制而产生的局限性。最后,我们从系统的角度讨论城市运输问题,包括诸如搭车、多式联运和可持续运输等全系统的挑战。