Article
Green & Sustainable Science & Technology
Peng Guo, Yanling Sun, Qiyi Chen, Junrong Li, Zifei Liu
Summary: This study utilizes taxi GPS data to analyze the impact of rainfall on residents' travels in urban areas. The results show significant changes in taxi flow and its spatial and temporal distribution pattern on rainy days, which affects transportation supply and demand. These findings may provide useful references for formulating urban transport policies that can adapt to different weather conditions.
Article
Environmental Studies
Alessia Calafiore, Krasen Samardzhiev, Francisco Rowe, Martin Fleischmann, Daniel Arribas-Bel
Summary: This study uses high spatio-temporal resolution data provided by Spectus.ai to investigate how the deprivation level of where people live influences their everyday activity choices. By analyzing GPS trajectories, the study finds that residents in different deprivation levels have different preferences for urban environments, with those in the most deprived areas being more exposed to urban-based functions and well-served areas, while those in the least deprived areas are more exposed to countryside and low-density areas.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2023)
Article
Public, Environmental & Occupational Health
Valerie Washington, Seth Guikema, Joi-Lynn Mondisa, Aditi Misra
Summary: Researchers developed a data-driven method to identify areas that experienced evacuations by inferring home locations of mobile phone users and comparing departure trends. This method helps detect changes in departure behavior before and after hurricanes, improving our understanding of evacuation patterns and enhancing planning.
Article
Environmental Sciences
Giovanna Fancello, Julie Vallee, Cedric Sueur, Frank J. van Lenthe, Yan Kestens, Andrea Montanari, Basile Chaix
Summary: The urban environment has a significant impact on the mental health of residents, with a focus on residential neighborhoods. Researchers in this study explored the effects of non-residential environments and the daily experience of urban spaces using a people-based approach focused on mobility paths. They found that momentary mental well-being is related to exposure to micro-urban spaces along daily mobility paths, especially when residents engage in leisure activities or active mobility and are exposed to walkable areas, water elements, and commerce, leisure, and cultural attractors.
ENVIRONMENT INTERNATIONAL
(2023)
Article
Construction & Building Technology
Ruoxi Wang, Nan Li, Yan Wang
Summary: In urban areas, there are two distinct subpopulations of returners and explorers whose mobility patterns are impacted by the duration of observation. This dependence can be explained by information accumulation, individuals' spatial exploration behaviors, and changes in individuals' important locations. These findings are essential for studying urban human mobility patterns for various purposes such as disease prediction and population behavioral modeling.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Chemistry, Analytical
Hua Chen, Ming Cai, Chen Xiong
Summary: The study analyzes urban traffic patterns and population distributions using license plate recognition (LPR) data and cellular signaling (CS) data, and examines the correlations between the two datasets. The results show that the population distribution and traffic patterns computed by the two datasets are fairly similar, providing a reliable basis for urban transport planning.
Article
Ecology
Zander S. Venter, Vegard Gundersen, Samantha L. Scott, David N. Barton
Summary: Recreational activity is a valuable ecosystem service with benefits for public health, but crowdsourced data from apps like Strava have inherent biases that make it difficult to generalize. In Oslo, Norway, Strava data accurately captured spatial and temporal variations in recreational activity, but it exhibited biases towards certain groups such as cyclists, males, and middle-aged people. Future studies using Strava data need to consider these biases, especially the underrepresentation of vulnerable age and socio-economic groups.
LANDSCAPE AND URBAN PLANNING
(2023)
Article
Urban Studies
Mahsa Najarsadeghi, Ehsan Dorostkar
Summary: This study examines the impact of virtual mobility on human mobility in Tehran's nightlife conditions, using Foursquare social media data. The research highlights the effects of Foursquare on nightlife and spatial interactions, emphasizing the importance of virtual mobility in shaping human behavior.
Review
Environmental Studies
Masahiko Haraguchi, Akihiko Nishino, Akira Kodaka, Maura Allaire, Upmanu Lall, Liao Kuei-Hsien, Kaya Onda, Kota Tsubouchi, Naohiko Kohtake
Summary: This article discusses the opportunities and challenges of using human mobility data and analysis to improve disaster risk reduction planning. It emphasizes the need for research on the human mobility of vulnerable populations, focusing on disaster mitigation and prevention, developing analytical methods for evidence-based disaster planning, integrating different types of data to overcome methodological challenges, and the importance of transdisciplinary knowledge co-production for evidence-based urban planning.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2022)
Article
Thermodynamics
Yapan Liu, Bing Dong
Summary: The buildings sector in the United States accounts for 76% of electricity consumption and 40% of primary energy use and associated greenhouse gas emissions. This study explores urban scale human mobility using three months of GPS data from 93,000 users in the Phoenix Metropolitan Area. The research develops models using a Density-Based Spatial Clustering algorithm and Long Short-Term Memory neural network to predict urban scale daily human mobility patterns with high accuracy and precision.
BUILDING SIMULATION
(2023)
Article
Transportation Science & Technology
Jinsoo Kim, Jae Hun Kim, Gunwoo Lee
Summary: The purpose of this study is to develop a mobility mode inference model that takes into account the sequential behaviors of choosing a mobility mode. By using long-term recurrent convolutional networks (LRCNs), the model considers the sequential behaviors in choosing the mobility mode over time. The results show that considering sequential behaviors enhances the model's performance in inferring the mobility mode, and the LRCN approach outperforms previous methods.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Computer Science, Software Engineering
Shuangyan Wang, Gang Mei, Salvatore Cuomo
Summary: This paper proposes a paradigm for mining human mobility patterns based on GPS trajectory data, using complex network analysis to quickly and effectively identify human mobility patterns.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Engineering, Civil
Zineb Mahrez, Essaid Sabir, Elarbi Badidi, Walid Saad, Mohamed Sadik
Summary: As cities expand rapidly, the need for smart city development becomes urgent. Intelligent transportation systems (ITS) combined with artificial intelligence technology can effectively optimize urban planning and address traffic issues. Political decisions and open data are crucial in promoting healthy and sustainable city development.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Emanuel Lima, Ana Aguiar, Paulo Carvalho, Aline Carneiro Viana
Summary: This study proposes using human mobility to inform offloading tasks during commuting. By analyzing granular mobility datasets from two cities, the study extracts Offloading Regions (ORs) and characterizes them based on offloading opportunity metrics. The results show that a significant portion of travel time is spent inside the extracted ORs. Predicting the next OR can improve offloading orchestration, but current models have poor predictive performance. The study highlights the need for offloading systems to adopt hybrid strategies and characterizes the trade-off between mobility predictability and offloading opportunities.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2022)
Article
Geography
Fang Liu, Wei Bi, Jinjun Tang, Wei Hao
Summary: This study explores the relationship between travel destinations and urban built environments using inhomogeneous Poisson point processes, and validates the effectiveness of the proposed method with taxi GPS trajectory data collected in Shenzhen City, China. The results of this study enhance understanding of the correlation between travel patterns and urban structure.
TRANSACTIONS IN GIS
(2022)
Review
Computer Science, Information Systems
Weifeng Lv, Bowen Du, Dianfu Ma, Tongyu Zhu, Chen Wang
FRONTIERS OF COMPUTER SCIENCE IN CHINA
(2010)
Proceedings Paper
Engineering, Electrical & Electronic
Qi Wang, Haitao Yu, Tongyu Zhu, Ge Li
2013 13TH INTERNATIONAL CONFERENCE ON ITS TELECOMMUNICATIONS (ITST)
(2013)
Proceedings Paper
Engineering, Electrical & Electronic
Tongyu Zhu, Jianjun Yu, Bowen Du
2012 INTERNATIONAL CONFERENCE ON CONNECTED VEHICLES AND EXPO (ICCVE)
(2012)
Proceedings Paper
Automation & Control Systems
Rong Ding, Xiaoguang Li, Tongyu Zhu, Zhenhan Zhong, Jufu Zhang
Article
Engineering, Multidisciplinary
Lue WeFeng, Zhu TongYu, Wu DongDong, Dai Hong, Huang Jian
SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES
(2008)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)