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
Computer Science, Information Systems
Merkouris Karaliopoulos, Eleni Bakali
Summary: This paper investigates the optimization of mobile end users' contributions to tasks in participatory mobile crowdsensing, taking into account the bounded rationality exhibited in human decision making. The authors model user choices as Fast-and-Frugal-Trees and propose novel optimization problems for nonprofit and for-profit platforms. Evaluation results show significant improvements in both platform revenue and task contributions when considering the lexicographic structure in human decision making.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Engineering, Manufacturing
Tarikere T. Niranjan, Narendra K. Ghosalya, Raveen R. Menon, Kristian Rotaru, Srinagesh Gavirneni
Summary: We present the findings of five controlled experiments on interventions to improve decision making in the newsvendor task. The use of eye-tracking technology and interviews reveals that human decision makers tend to rely on past demand predictions, even when they are independent and identically distributed. The interventions tested reduce this reliance, but do not completely eliminate it, suggesting that judgmental forecasting persists despite the interventions.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Computer Science, Hardware & Architecture
Mauro Passacantando, Giorgio Gnecco, Yuval Hadas, Marcello Sanguineti
Summary: This study introduces a new framework to investigate Braess' paradox, by utilizing cooperative games with transferable utility to evaluate the contribution of network resources to overall network performance.
Article
Management
Tingliang Huang, Zhe Yin
Summary: This paper investigates how probabilistic or opaque selling should be managed in a firm's operations over time. The research suggests that offering high-value products with a high probability followed by a lower probability is typically the optimal strategy.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2021)
Article
Psychology, Multidisciplinary
Steeven Villa, Thomas Kosch, Felix Grelka, Albrecht Schmidt, Robin Welsch
Summary: This study investigates the placebo effect of Augmentation Technologies. Thirty naive participants were told to be augmented or not while conducting a task. The results show a sustained belief of improvement and an increase in risk-taking conditional on heightened expectancy using Bayesian statistical modeling.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Article
Engineering, Electrical & Electronic
Qinfei Long, Junhong Liu, Feng Liu, Yunhe Hou
Summary: To mitigate failure risk, a dynamic thermal rating (DTR) sensor can be placed in transmission lines. This paper proposes a submodular optimization-based DTR placement model that considers Braess paradox. A model based on Markov probability and important sampling weight techniques is utilized to quantify failure risk efficiently. The risk model is then applied to analyze the conditions for Braess paradox and reformulate the risk mitigation model with estimation error. A computationally efficient algorithm is designed to solve this nonmonotone submodular optimization, providing a provable approximation guarantee.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Industrial
Xi Zhang, Haicheng Tu, Jianbo Guo, Shicong Ma, Zhen Li, Yongxiang Xia, Chi Kong Tse
Summary: This paper studies how to enhance power grid resilience and achieve quick recovery after extreme events by adjusting the operating modes of the grid and reconfiguring its components. A double-loop optimization strategy is proposed, utilizing an interior point method and a genetic algorithm to find the optimal topology for coordinating available resources most effectively.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Business
Hsiu Fen Tsai, Shih-Chieh Fang
Summary: This study aims to examine the risk-return paradox from the perspective of firm resources and emphasizes the role of risk-taking capabilities in moderating the relationship between risk-taking and performance. Tests were conducted using data from Taiwan listed companies in the information technology and electronics industries. The findings highlight the context-specific nature of the relationship between risk-taking and performance, dependent on a firm's risk-taking capabilities.
MANAGEMENT DECISION
(2023)
Article
Economics
Junxiang Xu, Jin Zhang, Jingni Guo
Summary: This paper proposes a traffic assignment model based on cumulative prospect theory, improves the comprehensive cumulative prospect value function, constructs a boundedly rational user equilibrium model, and designs a new algorithm to solve the model. The research results demonstrate the theoretical and practical significance of the model for solving traffic assignment problems under uncertain supply and demand conditions.
SOCIO-ECONOMIC PLANNING SCIENCES
(2021)
Article
Mathematics, Interdisciplinary Applications
Joel Weijia Lai, Kang Hao Cheong
Summary: This article explores the relationship between Parrondo's paradox and Simpson's paradox in risk-taking behavior and decision-making, and demonstrates their interaction through network analysis.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Multidisciplinary Sciences
Rujin Liao, Jing Zhang, Ruwen Tan, Yilin Wu, Minjiu Yu
Summary: Real estate developers in China exhibit bounded rational behaviors in different land auction formats, deviating from fully rational bidding. This study establishes reference utility and subjective decision probability models to characterize utility distortion and winning probability distortion in open-bid and sealed-bid land auctions. The results show that deviation from fully rational bidding increases with competition intensity, and cost-disadvantaged developers deviate less from standard bidding in the bounded rational model.
SCIENTIFIC REPORTS
(2023)
Article
Green & Sustainable Science & Technology
Liang Wang, Lei Zhao, Xiaojian Hu, Xinyong Zhao, Huan Wang
Summary: This paper investigates the influence of boundedly rational decision characteristics on travelers' route choice behavior. The concept of boundedly rational confidence level (BRCL) is redefined as the probability that a trip arrives between the acceptable earliest and latest arrival time on the shortest travel time budget (TTB). The paper proposes acceptable boundedly rational arrival thresholds and develops a reliability-based boundedly rational traffic equilibrium model (R-BRTE) considering both travel time reliability and acceptable arrival thresholds. The numerical results demonstrate the significant impact of travelers' bounded rationality on their route choice behavior and network performance.
Article
Economics
Heiner Schumacher, Heidi Christina Thysen
Summary: In this study, it is found that agent forming beliefs based on a misspecified subjective model may lead to biased beliefs, but under certain conditions, the agent can have correct beliefs on the equilibrium path, resulting in a non-exploitative optimal contract. The optimal contract only adjusts additional variables if they are informative about the action according to the agent's subjective model. The study further shows that misspecifications can affect the optimal contract, and the scope for belief biases depends on the agent's job, such as her position in the hierarchy.
THEORETICAL ECONOMICS
(2022)
Article
Business
Arielle Badger Newman, Sharon Alvarez
Summary: This paper discusses the foundation of management research in bounded rationality and highlights the limitations of Western, male-centric business models. It explores the constraints imposed on female entrepreneurs by bounded rationality and provides evidence through interviews with stakeholders in a specific social system.
JOURNAL OF BUSINESS VENTURING
(2022)
Article
Engineering, Civil
Yan Zhao, Wai Wong, Jianfeng Zheng, Henry X. Liu
Summary: This paper proposes a maximum likelihood estimation method for queue length estimation using historical probe vehicle data, solved iteratively by the EM algorithm. Validation results show that the method can accurately estimate the parameters, enabling cycle by cycle estimation of queue lengths.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Operations Research & Management Science
Xiaozheng He, Jian Wang, Srinivas Peeta, Henry X. Liu
Summary: This paper presents a discrete day-to-day signal retiming problem to fine-tune the green splits in a traffic network and reduce congestion and travel time.
NETWORKS & SPATIAL ECONOMICS
(2022)
Article
Transportation Science & Technology
Xingmin Wang, Yafeng Yin, Yiheng Feng, Henry X. Liu
Summary: This study proposes a new framework for max pressure control using reinforcement learning algorithms, considering phase switching loss and optimizing parameters. Simulation results show that the proposed control method outperforms traditional max pressure control. This research is of great significance for real-world implementations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Rusheng Zhang, Zhengxia Zou, Shengyin Shen, Henry X. Liu
Summary: This paper introduces a newly developed and deployed roadside cooperative perception system with an edge-cloud structure and multiple kinds of sensors. The performance of the system is analyzed using data collected from the field, and its potential in applications such as traffic volume monitoring and road safety warning is demonstrated.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Transportation Science & Technology
Jun Hua, Guangquan Lu, Henry X. Liu
Summary: This study establishes a driving behavior model framework to explain drivers' approaching behaviors to signalized intersections, and obtains probabilities and distributions through simulations. The results demonstrate the validity of the proposed model and its applicability to drivers with different desired risks.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Xingmin Wang, Zachary Jerome, Chenhao Zhang, Shengyin Shen, Vivek Vijaya Kumar, Henry X. Liu
Summary: This paper proposes a trajectory data processing pipeline for urban traffic network applications, which includes matching, splitting, and distance extraction steps, as well as smoothing and filtering algorithms to reduce noise and errors. The processed data is used to calculate various mobility performance indices for comprehensive evaluations. The proposed methods are efficient, robust, and scalable, and can be applied to large-scale urban traffic networks.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Environmental Studies
Xiaozheng He, Yu Wei, Jose Holguin-Veras
Summary: This paper proposes a simple imputation technique using the Brownian bridge structure to fill in missing speed data in low-resolution truck GPS datasets. The results demonstrate that the technique improves estimation accuracy in estimating fuel consumption and emissions using low-resolution GPS data.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Engineering, Civil
Xia Yang, Chenyang Wang, Xiaozheng He, Hedi Zhang, Guangming Xu
Summary: With the rapid growth of e-commerce and direct-to-consumer deliveries, the last-mile problem has become more noticeable. Smart parcel lockers, with their advantages in economies of scale and 24/7 contactless self-service, play a crucial role in solving this problem. However, due to poor planning, limited expansion, and unclear profit models, smart parcel locker suppliers in China have been experiencing significant economic losses. This study proposes a bilevel programming model to optimize the location of community smart parcel lockers, aiming to maximize the profit for the supplier and user satisfaction. The results provide theoretical support and practical guidance for third-party smart parcel locker suppliers to plan their investment budgets and optimize locker locations for maximum profit.
JOURNAL OF ADVANCED TRANSPORTATION
(2023)
Article
Multidisciplinary Sciences
Shuo Feng, Haowei Sun, Xintao Yan, Haojie Zhu, Zhengxia Zou, Shengyin Shen, Henry X. Liu
Summary: A critical bottleneck for autonomous vehicle development and deployment is the high costs required to validate safety in real-world driving. Researchers have developed an intelligent testing environment using AI-based agents to accelerate the safety validation process without bias. Their approach reduces testing time by orders of magnitude and can also be applied to other safety-critical autonomous systems.
Article
Engineering, Civil
Zhen Yang, Rusheng Zhang, Gaurav Pandey, Neda Masoud, Henry X. Liu
Summary: This work proposes a hierarchical vehicle behavior prediction framework that incorporates traffic signal information and models the interaction between vehicles. The framework predicts vehicle behaviors in two stages: discrete intention prediction and continuous trajectory prediction. It is designed to capture the difference among human drivers with parameterized driver characteristics.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Zhen Yang, Jun Ying, Junjie Shen, Yiheng Feng, Qi Alfred Chen, Z. Morley Mao, Henry X. Liu
Summary: This paper proposes a method to detect GPS spoofing attacks on connected vehicles (CVs) and autonomous vehicles (AVs) using domain knowledge in transportation and vehicle engineering. A computational-efficient driving model is constructed by learning from historical trajectories, and a statistical method is developed to measure the dissimilarities between observed and predicted trajectories for anomaly detection. The proposed method is validated on real-world datasets and shown to detect almost all attacks with low false positive and false negative rates.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Pengcheng Wang, Xinkai Wu, Xiaozheng He
Summary: This research explores the vulnerability of nonlinear vehicle platoons characterized by oscillatory behavior caused by external perturbations. A vibration-theoretic approach is proposed to characterize the platoon vulnerability and obtain the resonance frequency. The closed-form formulas of damping intensity and resonance frequency are derived through rigorous analysis. Simulation results show that overdamped platoons are more robust against perturbations, while underdamped platoons can be destabilized easily by perturbations at the resonance frequency.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Yujie Feng, Jiangtao Wang, Yasha Wang, Xu Chu
Summary: As a crucial part of public health system, population health monitoring plays a significant role in shaping health policies. However, the high cost of traditional data collection methods has led to the proposal of sparse-sampling-completion algorithms. Existing data-completion methods primarily focus on adjacent-spatial correlations, which may not accurately infer missing prevalence data in neighboring areas due to cost constraints. To address this problem, we propose a novel deep-learning-based prevalence inference model, SDA-GAIN (Spatial-attention and Demographic-augmented Generative Adversarial Imputation Network), which improves accuracy by learning health semantic space similarities between cross-space areas. SDA-GAIN utilizes a Transformer-based model to learn healthy semantic similarities and a GAN-based model for high-accuracy completion, with the addition of demographic data to enhance the model's ability in learning better health semantic representation through CNN. Extensive experiments demonstrate that SDA-GAIN outperforms other state-of-the-art approaches at low sampling rates (<30%), leading to significant cost savings. Moreover, the visualization of health semantic similarity learned by SDA-GAIN closely resembles real-life situations.
IEEE TRANSACTIONS ON BIG DATA
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jingxuan Yang, Honglin He, Yi Zhang, Shuo Feng, Henry X. Liu
Summary: This paper proposes an adaptive testing method using sparse control variates, which evaluates the performance of CAVs by adaptively utilizing testing results. It reduces estimation variance by adjusting testing results based on multiple linear regression techniques and optimizes regression coefficients for the CAV under test. The method applies sparse control variates to critical variables of testing scenarios and has been validated in high-dimensional overtaking scenarios, achieving a 30 times acceleration in the evaluation process.
2022 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)
(2022)
Article
Engineering, Mechanical
Yu Wei, Xiaozheng (Sean) He
Summary: Rapid advances in vehicle automation and communication technologies enable connected autonomous vehicles (CAVs) to cross intersections cooperatively, which could significantly improve traffic throughput and safety at intersections. This study proposes an adaptive vehicle control method to facilitate the formation of a virtual platoon and the cooperative crossing of CAVs, factoring demand variations at an isolated intersection.
INTERNATIONAL JOURNAL OF MECHANICAL SYSTEM DYNAMICS
(2022)
Article
Economics
Songyot Kitthamkesorn, Anthony Chen, Seungkyu Ryu, Sathaporn Opasanon
Summary: The study introduces a new mathematical model to determine the optimal location of park-and-ride facilities, addressing the limitations of traditional models and considering factors such as route similarity and user heterogeneity.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2024)
