No abstract

A transit ridership study is an essential part of sustainability, and can provide a deep understanding of people's travel patterns for efficient transportation development and urbanization. However, there is a lack of empirical studies comparing subway and taxi services, and their interactions within a city, that is to say, the interdependent transportation networks. Incorporating new data, this study aims to examine the spatial variation of urban taxi ridership due to the impacts of a new subway line operation opened in 2014 in Wuxi, China. We examine the spatial patterns and interactions of ridership in Wuxi by integrating taxi trajectory from GPS data and subway data from continuously collected fare transactions. The results indicated that the demand for taxi and subway usage is quite elastic with respect to both location and time, and the new subway's opening had more influence on areas adjacent to subway stations and urban center-suburban travel. Furthermore, increases in travel time and distance would increase the demand for subway, while taxi trips largely represented movements for those locations that the subway could not reach. This paper betters the understanding of travel patterns through large volumes of transportation data for sustainable urbanization policy design.

The increasing availability of urban trajectory data from the GPS-enabled devices has provided scholars with opportunities to study urban dynamics at a finer spatiotemporal scale. Yet given the multi-dimensionality of urban trajectory dynamics, current research faces challenges of systematically uncovering spatiotemporal and societal implications of human movement patterns. Particularly, a data-driven policy-making process may need to use data from various sources with varying resolutions, analyze data at different levels, and compare the results with different scenarios. As such, a synthesis of varying spatiotemporal and network methods is needed to provide researchers and planning specialists a foundation for studying complex social and spatial processes. In this paper, we propose a framework that combines various spatiotemporal and network analysis units. By customizing the combination of analysis units, the researcher can employ trajectory data to evaluate urban built environment dynamically and comparatively. Two case studies of Chinese cities are carried out to evaluate the usefulness of proposed conceptual framework. Our results suggest that the proposed framework can comprehensively quantify the variation of urban trajectory across various scales and dimensions.

No abstract

Abstract:This paper describes the design and implementation of an evacuation simulation model developed based on the Traffic Grid Model in NetLogo. In this model, different scenarios were tested in order to find out the best strategy within specific environments. The model is flexible and includes many parameters to adjust to environment conditions and agent rules. These parameters can be modified to study which driving factors contribute most to drivers' evacuation performance. This research also focuses on the method of results analysis and traffic performance evaluation for different combinations of two model parameters. In each experiment, we analysed metrics such as evacuation time and average car speed for each strategy under different population distribution patterns. The results showed that this model could reveal an effective evacuation strategy for realistic scenarios.