Article
Transportation Science & Technology
Renxin Zhong, Jianhui Xiong, Yunping Huang, Nan Zheng, William H. K. Lam, Tianlu Pan, Biao He
Summary: Recent research shows that trip-based models are more accurate at capturing network hyper-congestion compared to conventional macroscopic fundamental diagram (MFD) dynamics, but analyzing dynamic user equilibrium of departure time choice remains a challenge due to the complex mathematical structure. The study highlights significant differences in information support between basic trip-based models and traditional MFD models.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Economics
Wen-Long Jin
Summary: This paper introduces a new dynamical system that can adjust drivers' departure times and verifies its stability. The study also examines the impact of symmetrical and asymmetrical coefficients on the model.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Transportation
Yong Yang, Rui Jiang, Xiao Han, Bin Jia, Ziyou Gao
Summary: This study designed an experiment to explore the effects of staggered work hours on the departure time choice behavior of commuters. The experimental results indicated that the subjects' choice behavior deviates from the pure-strategy equilibrium and staggered work hours have a significant impact on travel costs.
TRAVEL BEHAVIOUR AND SOCIETY
(2022)
Article
Economics
Takashi Akamatsu, Kentaro Wada, Takamasa Iryo, Shunsuke Hayashi
Summary: This paper presents a systematic approach for analyzing the departure-time choice equilibrium problem in a single bottleneck with heterogeneous commuters. The study shows that the essential condition for emerging equilibrium sorting patterns is the Monge property of schedule delay functions, and equilibrium problems with this property can be solved analytically. The proposed approach can be applied to more general problems with multiple types of heterogeneities.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Transportation Science & Technology
Qiumin Liu, Rui Jiang, Wei Liu, Ziyou Gao
Summary: This study extends existing stochastic bottleneck model studies by considering a more general distribution of the bottleneck capacity. The results show that the mean travel cost and the mean total travel time may vary with the capacity degradation probability and level. It is also found that the mixed capacity distribution outperforms the binary capacity distribution in evaluating the departure/arrival pattern and mean travel cost.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Operations Research & Management Science
Mostafa Ameli, Mohamad Sadegh Shirani Faradonbeh, Jean-Patrick Lebacque, Hossein Abouee-Mehrizi, Ludovic Leclercq
Summary: Departure time choice models are crucial for determining traffic load in transportation systems. This study introduces a new framework based on mean field games theory to model and analyze the departure time user equilibrium (DTUE) problem without making assumptions on user characteristics or dynamic traffic models. The proposed continuous and discrete departure time choice models are compared with existing models, showing better solutions and faster convergence.
TRANSPORTATION SCIENCE
(2022)
Article
Transportation
Qiumin Liu, Dongxu Lu, Rui Jiang, Xiao Han, Ronghui Liu, Ziyou Gao
Summary: This study investigates the effects of environmental uncertainty on departure time choice behavior. The experimental results show that individuals tend to minimize their travel cost budget rather than their mean travel cost, and providing feedback on all departure times' costs leads to a smaller effect compared to only providing feedback on individuals' own costs.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Economics
Xiao-Shan Lu, Hai-Jun Huang, Ren-Yong Guo, Fen Xiong
Summary: This paper extends the work of Zhang et al. (2008) to investigate daily commuting patterns in a linear city, allowing for late arrival and early departure. A combined regime is proposed to reduce total social cost, with analytical results showing the impact of different factors on commuters' departure time choices.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Economics
Hongxing Ding, Hai Yang, Hongli Xu, Ting Li
Summary: Based on the status quo-dependent route choice model in Xu et al. (2017), this study integrates the model into traffic assignment modeling and establishes a Status quo-dependent User Equilibrium (SDUE) model. The SDUE model considers cognitive limitations, satisficing behavior, inertial behavior, and variation in value of time (VOTs) in route choice behavior. The study also demonstrates that equilibrium solutions from previous UE models can be included in the SDUE solution set by varying VOTs among users and scenarios.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Engineering, Civil
Shixu Liu, Jianchao Zhu, Said M. Easa, Lidan Guo, Shuyu Wang, Haoyu Wang, Yijian Xu
Summary: This study analyzed the utility calculation principles of travelers and proposed the MA-TC model, conducting a questionnaire survey. Results showed significant differences in model parameters under different circumstances, with the MA-TC model demonstrating higher predictive accuracy under deterministic and risky conditions.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Engineering, Civil
Markus Friedrich, Matthias Schmaus, Jonas Sauer, Tobias Zundorf
Summary: This paper investigates existing departure time models for a schedule-based transit assignment and their parametrization. It suggests using 1-minute intervals and introduces the concept of adaptation time. The study found that longer time intervals led to arbitrary run volumes, indicating the need for a nonlinear evaluation function to better describe passenger behavior.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Computer Science, Artificial Intelligence
Wenlong Zhu, Junting Zhang, Shunqiang Ye, Wanli Xiang
Summary: This paper investigates Braess Paradox under the bi-objective user equilibrium, introducing the definition and occurrence conditions of the paradox. Analytical properties of the bi-objective user equilibrium solutions and the conditions for the occurrence of Braess Paradox are explored on a classical Braess network. The study proves that the occurrence conditions of Braess Paradox are dependent upon link performance parameters and travel demand.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Civil
Shijun Yu, Siyuan Zhang, Shejun Deng, Tao Ji, Peng Zhou, Lang Peng
Summary: This study analyzed tourists' travel behavior based on a survey conducted in Yangzhou city and established a prediction model for tourists' departure time choice. The results indicated that synchronized traffic information and other tourism-related factors determine tourists' departure time choice, distinguishing it from the daily travel behavior of urban residents. This research can provide suggestions for the urban tourism management department to formulate more targeted and efficient policies while creating a more comfortable tourism environment for tourists.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Engineering, Multidisciplinary
A. Rasaizadi, S. Seyedabrishami
Summary: This study employed a joint model using copula functions to explore the interdependency between departure time and destination choices. Results suggested that there were common unobserved factors and observed factors between these decisions.
Article
Operations Research & Management Science
Ren-Yong Guo, Hai Yang, Hai-Jun Huang
Summary: We study a departure time choice model for commuters in a bottleneck system with heterogeneity in travel time and schedule delays. A Walrasian toll charge scheme is used to control traffic flows. The scheme is anonymous and does not require information on travel time and schedule delays. The theoretical analysis proves that the toll charge scheme can achieve the system optimum flow pattern. The distributions of traffic flows and toll charges at the system optimum state are shown analytically, and the scheme's effectiveness is examined through numerical analyses.
TRANSPORTATION SCIENCE
(2023)
Article
Multidisciplinary Sciences
Er-Jian Liu, Xiao-Yong Yan
SCIENTIFIC REPORTS
(2020)
Article
Computer Science, Software Engineering
Jian Zhou, Haoming Wang, Fu Xiao, Xiaoyong Yan, Lijuan Sun
Summary: This paper proposes a new network traffic prediction method based on ESN with adaptive reservoir (ESN-AR), which incorporates the idea of generative adversarial network (GAN) and feedforward neural network (FNN) to achieve accurate prediction of different network traffic characteristics.
SOFTWARE-PRACTICE & EXPERIENCE
(2021)
Article
Computer Science, Hardware & Architecture
Jian Zhou, Yang Chen, Fu Xiao, Xiaoyong Yan, Lijuan Sun
Summary: This paper proposes a water quality prediction method based on transfer learning and echo state network, which aims to improve prediction accuracy by utilizing water quality information from nearby monitoring points and taking advantage of the time sequence characteristics.
JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS
(2021)
Article
Mechanics
Hao Wang, Xiao-Yong Yan, Jinshan Wu
Summary: The social gravity law is widely observed in various domains, such as travel, migration, trade, communication, and collaboration. The law is explained by individual interaction and bounded rationality, with a free utility model proposed to provide a mathematical explanation. The model not only explains existing models but also extends to network interactions.
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT
(2021)
Article
Engineering, Manufacturing
Xiao Han, Yun Yu, Bin Jia, Zi-You Gao, Rui Jiang, H. Michael Zhang
Summary: The study found that transparent descriptive information helped in achieving efficient equilibrium and stabilizing choice behavior, historical experiences influenced initial choices and equilibrium selection, a higher barrier between the two equilibria hindered and prolonged the transformation to efficient equilibrium, and a deeper attraction basin of the efficient equilibrium was more appealing in equilibrium selection.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Computer Science, Information Systems
Jian Zhou, Xiaotian Gong, Lijuan Sun, Yong Xie, Xiaoyong Yan
Summary: This paper proposes an adaptive routing strategy based on improved double Q-learning for S-IoT, which optimizes the Q value, reward value, and discount factor to achieve more efficient and secure routing in highly dynamic environments.
SECURITY AND COMMUNICATION NETWORKS
(2021)
Article
Transportation Science & Technology
Yun Yu, Xiao Han, Bin Jia, Rui Jiang, Zi-You Gao, H. Michael Zhang
Summary: This paper investigates the welfare effects of inaccurate pre-trip information on commuters' departure time choice under stochastic bottleneck capacity. Three cases are studied: compliance, noncompliance, and co-existence. The benefits of inaccurate information depend on information quality, commuters' response and heterogeneity, and the frequency and severity of bottleneck capacity reductions.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Computer Science, Interdisciplinary Applications
Bing Song, Xiao-Yong Yan, Suoyi Tan, Bin Sai, Shengjie Lai, Hongjie Yu, Chaomin Ou, Xin Lu
Summary: Understanding the spatiotemporal characteristics of population movements during different time periods is important for urban planning, traffic engineering, and disease prevention. Using one-year long nationwide location-based service data in China, this study compares the applicability of five state-of-the-art human mobility models and finds significant periodicity and inequality in population flows across time and space. The comparison reveals that the parameter-free opportunity priority selection (OPS) model outperforms other models in characterizing human mobility in China across different types of days.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2022)
Article
Economics
Xiao Han, Yun Yu, Zi-You Gao, H. Michael Zhang
Summary: This paper examines the impact of uncertainty on transportation systems and travel costs, as well as the welfare effects of providing travel information in different scenarios. The results show that providing accurate information can improve welfare under certain traffic conditions, but may reduce welfare in specific situations. Factors such as the correlation between traffic conditions, frequency and severity of bottleneck drops, and the relationship between free-flow travel time and bottleneck capacity significantly affect the welfare effects of providing pre-trip information.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Economics
Yitao Yang, Bin Jia, Xiao-Yong Yan, Jiangtao Li, Zhenzhen Yang, Ziyou Gao
Summary: This paper proposes a data-driven method for identifying trip ends based on heavy truck GPS data in China. By capturing truck trajectory characteristics and analyzing temporal characteristics of truck activities, combined with GPS data, POI data, and highway network GIS data, the accuracy and analysis effectiveness of intercity freight trip data of heavy trucks are significantly improved.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Transportation Science & Technology
Yitao Yang, Bin Jia, Xiao-Yong Yan, Rui Jiang, Hao Ji, Ziyou Gao
Summary: In this study, a data-driven method is proposed to identify the origins and destinations of freight trips by analyzing a large amount of heavy truck GPS trajectories. By objectively defining speed and time thresholds and considering the city freight context and activity patterns, the accuracy of the method is improved.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Physics, Multidisciplinary
Xiang-Yu Jia, Er-Jian Liu, Chun-Yan Chen, Zhengbing He, Xiao-Yong Yan
Summary: This paper proposes a parameter-free interactive city choice (ICC) model for measuring intercity interaction from the perspective of individual choice behavior. The ICC model calculates the intercity interaction intensity based on the number of opportunities in the destination city, the number of intervening opportunities, and travel time. The model is applied to measure the interaction intensity among 339 cities in China and analyze the impact of changes in the land transportation network on intercity and city interaction intensity.
FRONTIERS IN PHYSICS
(2022)
Article
Transportation Science & Technology
Yong Yang, Xiao Han, Rui Jiang, Bin Jia, Zi-You Gao
Summary: This study investigates the competition and coordination behavior in public transport mode choice, finding that providing more information may lead to worse outcomes, and provides an adaptive learning model to explain this phenomenon.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Operations Research & Management Science
Rui Jiang, Xiao Han, Xiao-Yan Sun, Kai-Jia Sun, Wen-Xu Wang, H. M. Zhang, Bo-Yu Zhang, Zi-You Gao
Summary: Car use restrictions have been implemented in some large cities to tackle the growing number of cars and worsening traffic congestion. However, most of these restrictions do not offer flexibility to car owners in choosing the days they cannot drive. This paper studies a flexible car use restriction policy where car owners can choose the restricted day of the week. Theoretical results and laboratory experiments show that this flexible policy reduces average travel cost with a lower increase in average driving cost compared to traditional car use restrictions.
TRANSPORTATION SCIENCE
(2023)
Article
Computer Science, Information Systems
Yun Yu, Xiao Han, Rui Jiang, Justin Darr, Bin Jia
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)