相关论文: Short-distance commuters in the smart city
Many modern and growing cities are facing declines in public transport usage, with few efficient methods to explain why. In this article, we show that urban mobility patterns and transport mode choices can be derived from cellphone call…
Walking and cycling, commonly referred to as active travel, have become integral components of modern transport planning. Recently, there has been growing recognition of the substantial role that active travel can play in making cities more…
In transport modeling and prediction, trip purposes play an important role since mobility choices (e.g. modes, routes, departure times) are made in order to carry out specific activities. Activity based models, which have been gaining…
Traditional measures of urban accessibility often rely on static models or survey data. However, location information from mobile networks now enables large-scale, dynamic analyses of how people navigate cities. This study uses eXtended…
The metro system is playing an increasingly important role in the urban public transit network, transferring a massive human flow across space everyday in the city. In recent years, extensive research studies have been conducted to improve…
Recent advances in data collection and technology enable a deeper understanding of complex urban commuting, yet few studies have rigorously analyzed the temporal stability and Origin-Destination (OD) heterogeneity of route choice. To…
As more and more people continue to live in highly urbanised areas across the globe, reliable accessibility to amenities and services plays a vital role in sustainable development. One of the challenges in addressing this issue is the…
Existing studies have extensively used spatiotemporal data to discover the mobility patterns of various types of travellers. Smart card data (SCD) collected by the automated fare collection systems can reflect a general view of the mobility…
While analysis of urban commuting data has a long and demonstrated history of providing useful insights into human mobility behavior, such analysis has been performed largely in offline fashion and to aid medium-to-long term urban planning.…
Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper…
This paper proposes a self-calibrated transit service monitoring framework that aims to obtain the performance of a transit system using automated collected data. We first introduce an event-based transit simulation model, which allows the…
Microsimulation based frameworks have become very popular in many research areas including travel demand modeling where activity-based models have been in the center of attention for the past decade. Advanced activity-based models…
Location-based social network data offers the promise of collecting the data from a large base of users over a longer span of time at negligible cost. While several studies have applied social network data to activity and mobility analysis,…
World population growing in conjunction with the preference to live in the cities; make the city management a challenging issue. Traditional Cities with their common features will not be able to handle the human needs. As a result, smart…
The increasing availability and adoption of shared vehicles as an alternative to personally-owned cars presents ample opportunities for achieving more efficient transportation in cities. With private cars spending on the average over 95\%…
We study a new random search process: the \textit{taxi-drive}. The motivation for this process comes from urban sensing, in which sensors are mounted on moving vehicles such as taxis, allowing urban environments to be opportunistically…
Learning behavior mechanism is widely anticipated in managed settings through the formal syllabus. However, heading for learning stimulus whilst daily mobility practices through urban transit is the novel feature in learning sciences.…
This study presents an initial framework for distinguishing group and single pedestrians based on real-world trajectory data, with the aim of analyzing their differences in space utilization and emergent behavioral patterns. By segmenting…
Human mobility is subject to collective dynamics that are the outcome of numerous individual choices. Smart card data which originated as a means of facilitating automated fare collections has emerged as an invaluable source for analyzing…
The preponderance of connected devices provides unprecedented opportunities for fine-grained monitoring of the public infrastructure. However while classical models expect high quality application-specific data streams, the promise of the…