Article
Computer Science, Artificial Intelligence
Liu Yang, Ao Li
Summary: This study establishes a multi-agent route choice model to investigate the impact of travelers' adaptive adjustment behaviors on traffic network flow diversion under the assumption of bounded rationality, using cumulative prospect theory and evolutionary cellular automata. The model divides travelers into risk-seeking and risk-aversion types and designs dynamic reference points based on the reliability of travel time and the idea of cellular genetic algorithm. Finally, a multi-agent bounded rational route choice evolution algorithm is developed to solve the problem of traffic flow assignment in a road network by combining the evolution rule of multi-agent reference points with the traditional method of successive average algorithm. The main contributions of this research show that the evolution model has well inherited the characteristics of the route flow diversion in the traditional model.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Thermodynamics
Gokturk Poyrazoglu, Elvin Coban
Summary: The stochastic value estimation tool is developed for electrical and financial valuation of electric vehicle charging points, serving as a planning and research tool with detailed data on station and vehicle usage. The analysis of a case study at one of the biggest shopping malls in Istanbul, Turkey, provides insights on station performance metrics and related indicators.
Article
Engineering, Industrial
Minghui Cheng, Dan M. Frangopol
Summary: Reliability-, risk-, and utility-based life-cycle maintenance is a normative approach for rational decision-making regarding structural systems under uncertainty. Cumulative prospect theory (CPT) is a popular model to describe people's decisions under risk, capturing attitudes towards high consequence and low probability associated with structural failure. Parameters of CPT need to be calibrated for specific contexts, as they can significantly affect optimal decisions under riskier plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(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
Computer Science, Artificial Intelligence
Ying Li, Peide Liu, Xiaoming Wu
Summary: This paper develops an FMEA framework based on the dynamic reference point cumulative prospect theory, considering the risk attitudes of FMEA experts. The proposed method enhances the flexibility and reliability of risk assessment by taking into account the different and dynamic risk attitudes of experts.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Multidisciplinary Sciences
Alexandre Pastor-Bernier, Arkadiusz Stasiak, Wolfram Schultz
Summary: This study demonstrates that satiety affects reward value coding and that Revealed Preference Theory may offer a solution to assess economic reward value. Neuronal signals in the OFC closely track subjective value changes, supporting the idea of subjective economic reward value coding in OFC neurons.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Economics
Kexin Geng, Yacan Wang, Elisabetta Cherchi, Pablo Guarda
Summary: This paper aims to provide empirical evidence to define the shape parameters in cumulative prospect theory (CPT) for car commuters' departure time choice behavior under congestion charge scenarios. The results suggest that commuters' departure time choice under the congestion charge policy is consistent with the assumption of CPT. The findings shed light on travelers' behavioral responses to congestion charge schemes and provide an important empirical reference.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Computer Science, Artificial Intelligence
Junxiang Xu, Jingni Guo, Jin Zhang, Weihua Liu, Hui Ma
Summary: This study uses cellular automata and cumulative prospect theory to establish a travel route choice model, analyzing the impact of bounded rational travel behavior on route choice. By focusing on the transportation network in the Sichuan Tibet region, the study provides a theoretical framework and algorithm to guide transportation organization and support regional transportation planning and traffic control schemes in the future.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Substance Abuse
E. T. Curtis, J. L. Curtis
Summary: Problem gambling is a non-substance-based addictive disorder that can cause significant distress and dramatic consequences. We apply Cumulative Prospect Theory (CPT) to provide a formal analysis of cognitive distortions in problem gambling. Our experiments suggest that problem gambling is associated with a shallow valuation curve, a reversal of loss aversion, and decreased influence of subjective value on decisions (i.e., more noise or variability in preference).
JOURNAL OF GAMBLING STUDIES
(2023)
Article
Transportation
Lawrence Christopher Duncan, David Paul Watling, Richard Dominic Connors, Thomas Kjaer Rasmussen, Otto Anker Nielsen
Summary: This paper introduces a new route choice modelling framework that effectively deals with route correlations and unrealistic routes by integrating correlation-based Path Size Logit model with Bounded Choice Model (BCM). The derived Bounded Path Size (BPS) model provides improved fit relative to non-bounded versions and BCM, demonstrating computational feasibility in parameter estimation.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Engineering, Multidisciplinary
Chengzhi Qu, Yan Zhang, Feifan Ma, Kun Huang
Summary: In this paper, an evolutionary optimization algorithm based framework is introduced to automatically obtain the parameter configuration of point clouds denoising methods. New no-reference quality assessment metrics are proposed to evaluate the point clouds quantitatively during the optimization process. Experimental results show that the automatic tuning parameters provide a significant boost in performance compared to manual tuning parameters.
Article
Mathematics, Interdisciplinary Applications
Dongmei Yan, Yang Yang
Summary: The study introduces a multiclass cumulative prospect value-based cross-nested logit stochastic user equilibrium model and proves the existence and equivalence of model solutions. Different methods are designed and compared, showing that the CPV-based model is more aligned with real-world scenarios.
DISCRETE DYNAMICS IN NATURE AND SOCIETY
(2021)
Article
Economics
Matthew Kovach, Elchin Suleymanov
Summary: We explore how a reference point can direct attention and provide a behavioral framework for the Reference-Dependent Random Attention Model (RD-RAM). Our results show that preferences can be uniquely identified even when the attention process depends on both the menu and the reference point. We also analyze specific attention processes and characterize reference-dependent versions of several prominent models, illustrating their ability to explain observed behavioral patterns.
JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION
(2023)
Article
Transportation Science & Technology
Yunhe Tong, Nikolai W. F. Bode
Summary: This study introduces a mathematical model to investigate the decision-making processes in sequences of consecutive pedestrian route choices. It found that the sensitivity to environmental information diminishes as pedestrians make more sequential decisions, particularly when only information on the movement of others is available. The findings suggest that this diminishing sensitivity may lead to more predictable route choice dynamics across pedestrian crowds.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Public, Environmental & Occupational Health
Dongli Gao, Wei Xie, Ruifeng Cao, Eric Wai Ming Lee, Richard Kwok Kit Yuen, Jingwen Weng
Summary: Exit choice is crucial for pedestrian safety and evacuation efficiency in emergencies. This paper contributes by using cumulative prospect theory to predict exit choice and summarizing and examining different decision-making rules. The predictions from Max and Expo showed higher realism, while the results from Ratio were more robust, as indicated by the parameters of Accuracy and F1-score.
JOURNAL OF SAFETY SCIENCE AND RESILIENCE
(2023)
Article
Operations Research & Management Science
Hongli Xu, Hai Yang, Jing Zhou, Yafeng Yin
TRANSPORTATION SCIENCE
(2017)
Article
Economics
Hongli Xu, Yingyan Lou, Yafeng Yin, Jing Zhou
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2011)
Article
Engineering, Civil
Md. Shahid Mamun, Hongli Xu, Yafeng Yin
TRANSPORTATION RESEARCH RECORD
(2011)
Article
Transportation
Hongli Xu, William H. K. Lam, Jing Zhou
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2014)
Article
Management
Yuhao Liu, Hongli Xu, Xinlian Yu, Jing Zhou
Summary: This study presents a heuristic strategy that utilizes weather information to improve feeder-bus operation. By establishing the relationship between weather information and expected passenger arrival rates, an optimization model is developed to minimize passengers' waiting time cost and feeder bus operating cost. A chance constraint is introduced to control overloading risk, ensuring a high level of service. Numerical experiments demonstrate the advantages of the proposed heuristic strategy.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Engineering, Civil
Xinlian Yu, Alireza Khani, Jingxu Chen, Hongli Xu, Haijun Mao
Summary: This study presents a robust deep reinforcement learning approach for real-time network-wide holding control and evaluates its effectiveness in a simulator. The results show significant achievements in reducing computation time and waiting time, as well as exhibiting better robustness.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
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
Environmental Studies
Xuedong Wang, Ziqi Song, Hongli Xu, Hua Wang
Summary: The recent advancements in fast charging technology have allowed electric buses to be recharged at bus stops while passengers board and alight. To reduce en-route charging costs, facility sharing among buses from multiple lines is considered, but this may lead to charging conflicts. This study explores the planning and scheduling of charging infrastructure for battery electric bus (BEB) systems, with a focus on en-route charging and charging conflict avoidance. Mathematical models are proposed to determine the charging schedule and infrastructure planning, which are then formulated as linear mixed-integer programs. Numerical examples demonstrate that the proposed models can efficiently solve the problem in large BEB systems and achieve cost-effective en-route charging.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
