What is analysis technique for human mobility on transportation ?5 answersAnalysis techniques for human mobility in transportation include network modeling methods, clustering and segmentation techniques, and the use of smart card data. Network modeling methods, such as the Multiple Regression Quadratic Assignment Procedure and Stochastic Actor-Oriented Models, can be used to analyze the effect of spatial and context attributes on individual movement patterns. Clustering and segmentation techniques are used to group public transport users based on their temporal or spatial-temporal characteristics, allowing for the characterization of individual stations, lines, or urban areas. Smart card data, originally used for automated fare collection, has emerged as a valuable source for analyzing human mobility patterns and can be used for various applications, including market segmentation and analysis of urban activity locations. These techniques provide insights into travel patterns, support decision-making for service planning and policy evaluation, and enhance the understanding of users' travel patterns.
How to visualize the data of traffic accidents?5 answersTo visualize the data of traffic accidents, various techniques and tools can be used. One approach is to construct a knowledge graph based on the case data of traffic accidents, which includes multidimensional dynamic and static factors. Another method is to develop a dynamic data visualization system using JavaScript and Data-Driven Documents (D3) to model the number of motor vehicle occupant fatalities, considering multiple variables such as age, sex, and impaired driving. Python programming language and libraries like Pandas, NumPy, Matplotlib, and Seaborn can also be utilized for visualization purposes. Additionally, a traffic accident visualization tool can be created, integrating techniques such as interactive maps, word clouds, histograms, donut charts, and calendars. Business Intelligence (BI) solutions can also be employed to provide visual data exploration for authorities to analyze and make informed decisions about traffic accidents.
What is mobility?5 answersMobility is a broad term that refers to the ability to move around and change positions, such as walking, rising from a chair, and maintaining balance while standing. It is a key determinant of overall health and quality of life, particularly in older individuals. Mobility limitations increase with age, and exercise-based rehabilitation interventions, including mobility and balance training, have been shown to be effective in improving mobility in individuals with frailty. In addition, mobility has different meanings in various science disciplines. In economics, it refers to the ability to improve economic status in relation to income and wealth. In information systems and computer science, it is used to describe the concept of mobile computing. Mobility is also crucial in logistics for the transportation of people and goods. Furthermore, mobility plays a significant role in urban planning, optimizing transportation systems and meeting different mobility needs. Overall, mobility is a multifaceted concept that encompasses physical movement, economic status, technological advancements, and urban planning.
How can social mobility beliefs be measured?4 answersSocial mobility beliefs can be measured using various methods. One approach is through the use of questionnaire items that ask individuals to estimate the rate of upward social mobility in a given population. These subjective perceptions can be measured by asking respondents to divide the population into different segments, such as thirds or quintiles, and estimate the percentage of individuals who improve their socio-economic standing. Another method involves analyzing social media data, such as geotagged messages on Twitter, to capture beliefs about social distancing and its impact on mobility. Additionally, subjective mobility can be assessed through surveys and interviews, allowing individuals to express their perceptions, explanations, and assessments of their own social trajectory. These different approaches provide insights into how individuals perceive and understand social mobility, highlighting the importance of considering both objective and subjective measures in studying this phenomenon.
Is there any Mobility model for Human Mobility Analysis?5 answersHuman mobility models for analysis have been developed using various approaches. One approach is the use of General Purpose Transformers (GPT) and Graph Convolutional Networks (GCNs). These models have shown promising results in image analysis and natural language processing. Another approach involves the fusion of different data sources, such as cellular phone data and road traffic sensor data, to improve prediction accuracy. Additionally, a novel framework called SpatioTemporal-Augmented gRaph neural networks (STAR) has been proposed to capture the dynamic spatiotemporal effects of locations in human mobility simulation. Furthermore, an open-source dataset of human mobility trajectories has been created to facilitate the development and evaluation of human mobility prediction models. These models and datasets contribute to the advancement of human mobility analysis and prediction.
What are all the studies that discuss human mobility in terms of topological network structure.?4 answersStudies by Wiedemann et al., Lamosa et al., Cao et al., and the study on Hurricane Idadiscuss human mobility in terms of topological network structure. Wiedemann et al. propose using network modeling methods to analyze the effect of spatial and context attributes on individual movement patterns, using Multiple Regression Quadratic Assignment Procedure and Stochastic Actor-Oriented Models. Lamosa et al. study topological indexes and community structure changes in a business day using a mobility database with high temporal resolution. Cao et al. present a data-driven approach for characterizing urban mobility networks based on massive-scale mobile phone tracking data, constructing global urban mobility networks and motif-dependent urban mobility subnetworks. The study on Hurricane Ida examines human mobility network resilience at macroscopic, substructure, and microscopic scales.