Related papers: Understanding Cycling Mobility: Bologna Case Study
Predicting cycling duration for a given route is essential for training planning and event preparation. Existing solutions rely on physics-based models that require extensive parameterization, including aerodynamic drag coefficients and…
The rapid urbanization and increasing traffic have serious social, economic, and environmental impact on metropolitan areas worldwide. It is of a great importance to understand the complex interplay of road networks and traffic conditions.…
Urban vibrancy is the dynamic activity of humans in urban locations. It can vary with urban features and the opportunities for human interactions, but it might also differ according to the underlying social conditions of city inhabitants…
Traffic jams in urban scenarios are often caused by bottlenecks related to the street topology and road infrastructure, e.g. traffic lights and merging of lanes. Instead of addressing traffic flow optimization in a static way by extending…
Human mobility patterns deeply affect the dynamics of many social systems. In this paper, we empirically analyze the real-world human movements based GPS records, and observe rich scaling properties in the temporal-spatial patterns as well…
In this paper, we extend some ideas of statistical physics to describe the properties of human mobility. From a physical point of view, we consider the statistical empirical laws of private cars mobility, taking advantage of a GPS database…
The massive amounts of geolocation data collected from mobile phone records has sparked an ongoing effort to understand and predict the mobility patterns of human beings. In this work, we study the extent to which social phenomena are…
Road conditions affect both machine and human powered modes of transportation. In the case of human powered transportation, poor road conditions increase the work for the individual to travel. Previous estimates for these parameters have…
Urban mobility in developing countries, particularly in cities like Cali, Colombia, faces multifaceted challenges influenced by socioeconomic factors and the distinct characteristics of transport users Despite motorcycles emerging as a…
Understanding factors that influence software development velocity is crucial for engineering teams and organizations, yet empirical evidence at scale remains limited. A more robust understanding of the dynamics of cycle time may help…
While a social event, such as a concert or a food festival, is a common experience to people, a natural disaster is experienced by a fewer individuals. The ordinary and common ground experience of social events could be therefore used to…
Predicting human displacements is crucial for addressing various societal challenges, including urban design, traffic congestion, epidemic management, and migration dynamics. While predictive models like deep learning and Markov models…
Bike-sharing systems are a means of smart transportation in urban environments with the benefit of a positive impact on urban mobility. In this paper we are interested in studying and modeling the behavior of features that permit the end…
Bikesharing has gradually become one adopted sustainable transportation mode recent years to bring us many social, environmental, economic, and health-related benefits and rewards. There is increased research toward better understanding of…
Despite paying special attention to the motorcycle-involved crashes in the safety research, little is known about their pattern and impacts in developing countries. The widespread adoption of motorcycles in such regions in tandem with the…
As a newly-emerging travel mode in the era of mobile internet, ride-hailing that connects passengers with private-car drivers via an online platform has been very popular all over the world. Although it attracts much attention in both…
The description of complex human mobility patterns is at the core of many important applications ranging from urbanism and transportation to epidemics containment. Data about collective human movements, once scarce, has become widely…
Rapid urbanization and growing vehicle ownership exacerbate traffic congestion and prolong commute times. We examine the self-organizing dynamics of residential choice via a hypothetical home-swapping process to mitigate peak-hour traffic…
In recent years, an increasing number of shared E-bikes have been rolling out rapidly in our cities. It therefore becomes important to understand new behaviour patterns of the cyclists in using these E-bikes as a foundation for the novel…
Excess or wasteful commuting is measured as the proportion of actual commute that is over minimum (optimal) commute when assuming that people could freely swap their homes and jobs in a city. Studies usually rely on survey data to define…