Article
Computer Science, Artificial Intelligence
Xiao-Wei Chen, Bi Yu Chen, William H. K. Lam, Mei Lam Tam, Wei Ma
Summary: This paper introduces a bi-objective reliable path-finding algorithm for routing battery electric vehicles, taking into account the uncertainties of energy consumption and travel time. By decomposing the optimization problem into two sub-problems and proposing a novel ranking algorithm, the efficacy and efficiency of the algorithm are demonstrated through a case study on Hong Kong's road network.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Energy & Fuels
Wenxin Teng, Yi Zhang, Xuan-Yan Chen, Xiaoqi Duan, Qiao Wan, Yue Yu
Summary: This study proposes a reliable path-finding algorithm to improve fuel efficiency and reduce traffic-related CO2 emissions in stochastic networks.
Article
Engineering, Multidisciplinary
Sun Xie, Haixing Zhao, Jun Yin
Summary: This article explores the uniformly most reliable three-terminal graph of dense graphs with specific numbers of vertices and edges, discussing the existence and construction methods of locally most reliable and uniformly most reliable graphs under different conditions.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Engineering, Civil
Lijuan Shi, Siqi Zhou, Yuntao Chang, Qirui Zhang
Summary: This study quantitatively investigates the effects of intersections and different periods on tram travel-time reliability. The results show that lognormal distribution describes the tram travel time better than normal and gamma distributions. scenarios with no intersections, one intersection, and off-peak hours have higher reliability, while scenarios with two intersections and three intersections have low reliability. An optimized signal-control strategy based on travel-time reliability is proposed and validated through VISSIM simulation.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Mathematics, Applied
Sun Xie, Haixing Zhao, Liming Dai, Jun Yin
Summary: This article investigates the locally most reliable simple sparse three-terminal graphs and determines the most reliable three-terminal graphs under specific conditions. The research findings provide helpful guidance for constructing highly reliable networks.
Article
Engineering, Multidisciplinary
Pei-Pei Li, Yan-Gang Zhao, Zhao Zhao
Summary: This study proposes an efficient and accurate method to quantify failure probability considering the uncertainty of distribution parameters in structural reliability analysis. The method integrates the probability space of the conditional reliability index to obtain predictive failure probability, providing a complete picture of structural reliability evaluation results.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Industrial
Cheng-Ta Yeh, Yi-Kuei Lin, Louis Cheng-Lu Yeng, Pei-Tzu Huang
Summary: Railway trains are the preferred option for travelers, and the capacity of seats or cabins in the railway transportation system should consider stochasticity. System reliability is an important decision indicator for travel agents and can be evaluated using a minimal paths algorithm.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Metallurgy & Metallurgical Engineering
Liang Shen, Fei-ran Wang, Lei Hu, Xin-yi Lyu, Hu Shao
Summary: This paper investigates the consideration of travel time variation for rescue vehicles in the field of emergency management research. It proposes an optimal reliable path finding (ORPF) model that takes into account the uncertainties of travel time and link correlations, and explores how to optimize rescue vehicle allocation to minimize rescue time under uncertain conditions. The results highlight the importance of considering travel time reliability in allocation schemes.
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2022)
Article
Engineering, Industrial
Khanh T. P. Nguyen, Kamal Medjaher, Christian Gogu
Summary: In this paper, a new probabilistic deep learning methodology is presented for uncertainty quantification of multi-component systems' Remaining Useful Life (RUL). By utilizing the RUL distributions of the components and the information about the system's architecture, the proposed methodology achieves accurate point predictions and effective uncertainty management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Computer Science, Theory & Methods
Sun Xie, Haixing Zhao, Jun Yin
Summary: The paper discusses the reliability of two-terminal graphs and proves that there is no uniformly most reliable two-terminal graph under certain conditions.
THEORETICAL COMPUTER SCIENCE
(2021)
Article
Engineering, Civil
Hongliang Guo, Xuejie Hou, Zhiguang Cao, Jie Zhang
Summary: This paper investigates the reliable shortest path problem in Gaussian process regulated transportation networks, proposing the GP3 algorithm and demonstrating its superior performance through extensive experiments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Industrial
Wei-Chang Yeh
Summary: Everyday life is heavily reliant on various types of networks, and network reliability plays a crucial role in evaluating network performance. Existing studies mainly focus on the budget limit for each minimal path without considering the total budget of the entire network. This study proposes a novel concept and algorithm to build a more reliable binary-state network under the budget limit.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Information Systems
Lorena Anghel, Florian Cacho
Summary: This paper explores the full adaptive AVS, ABB, and combined supply and body bias techniques based on embedded monitors to improve circuit reliability and lifetime while reducing power consumption. SPICE simulations on ARM processors show that large design margins in terms of area and power can be reduced, while maintaining target reliability and performance.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2022)
Article
Computer Science, Hardware & Architecture
Baili Zhang, Keke Ling, Pei Zhang, Zhao Zhang, Mingjun Zhong
Summary: This paper proposes a set of MRMF algorithms, including NWCD, SCPDAT, and SCPDAP, for calculating the most reliable maximum flow from the edge cache node to the requesting node in a CDN. These algorithms improve time cost, reliability, and applicability compared to SDBA.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2022)
Article
Neurosciences
Eva Lopez-Rivera, Juan Jose Gonzalez-Badillo, Vanesa Espana-Romero
Summary: The study found that 8 mm edge depth seemed to be the most accurate for evaluating hanging time. For climbers of different levels, 10 mm or 12 mm edge depths were recommended based on their climbing abilities.
Article
Economics
Simon Oh, Ravi Seshadri, Carlos Lima Azevedo, Nishant Kumar, Kakali Basak, Moshe Ben-Akiva
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2020)
Article
Computer Science, Interdisciplinary Applications
Simon Oh, Antonis F. Lentzakis, Ravi Seshadri, Moshe Ben-Akiva
Summary: This paper investigates the network impacts of AMOD through high-fidelity traffic simulation, exploring traffic dynamics and environmental impacts in the case study of Singapore. The findings suggest that the introduction of AMOD may bring about significant impacts on network performance, including increased VKT, additional travel delay, and energy consumption, while reducing vehicle emissions. Despite the increase in network congestion, production of passenger flows remains relatively unchanged.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Transportation Science & Technology
Haizheng Zhang, Ravi Seshadri, A. Arun Prakash, Constantinos Antoniou, Francisco C. Pereira, Moshe Ben-Akiva
Summary: Simulation-based Dynamic Traffic Assignment models have important applications in real-time traffic management and control. This paper addresses challenges in online calibration using the Extended Kalman Filter (EKF) for large and congested networks, proposing methods to improve accuracy and scalability. By revisiting the concept of state augmentation and introducing a graph-coloring method, enhancements in prediction accuracy and computational performance were demonstrated through experiments and a case study.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Civil
Karina Hermawan, Ravi Seshadri, Takanori Sakai, P. Christopher Zegras, Moshe Ben-Akiva
Summary: This research examines people's willingness to adopt automated mobility-on-demand (AMoD) ride services and how it will affect their travel behaviors and activity patterns. The study finds that people are inclined to use AMoD services, but their propensity decreases with more usage. Young, frequent users of ride-hailing services without private cars are more likely to use AMoD. However, using this service may increase travel and travel costs.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Transportation
Renming Liu, Siyu Chen, Yu Jiang, Ravi Seshadri, Moshe Ben-Akiva, Carlos Lima Azevedo
Summary: This study proposes a tradable credit scheme for congestion management, which is based on trips and areas. The scheme allows credits to be traded between travelers and the regulator through a credit market. The research finds that the proposed scheme achieves the same social welfare as congestion pricing while maintaining revenue neutrality, and it is superior to area-based schemes.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Business
Andre Alho, Simon Oh, Ravi Seshadri, Giacomo Dalla Chiara, Wen Han Chong, Takanori Sakai, Lynette Cheah, Moshe Ben-Akiva
Summary: This study focuses on the parking choices of freight vehicles in large urban freight traffic generators and proposes an agent-based simulation approach to understand the impact of parking choices on externalities such as traffic congestion. A case study in a commercial region in Singapore shows that demand management strategies can improve travel time and reduce queuing.
RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT
(2022)
Article
Business
Simon Oh, Daniel Kondor, Ravi Seshadri, Diem-Trinh Le, Andre Romano Alho, Meng Zhou, Moshe Ben-Akiva
Summary: The emergence of ride-sourcing services has changed travel behavior and has implications for future urban mobility. However, there is a lack of empirical studies on the operational characteristics of ride-sourcing systems. This paper analyzes the operations of ride-sourcing using data from Singapore and finds reproducible patterns in demand, high demand during peak periods, and pricing surges. Shift behavior and user metrics also impact fleet operations and revenue.
RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT
(2022)
Article
Transportation Science & Technology
Ravi Seshadri, Andre de Palma, Moshe Ben-Akiva
Summary: This paper examines the application of tradable credit schemes in transportation and finds that tolling in tokens outperforms tolling in dollars under severe congestion. The study also highlights the importance of rational selling behavior in the market to avoid welfare losses in the quantity control system.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Economics
Giovanni Calabro, Andrea Araldo, Simon Oh, Ravi Seshadri, Giuseppe Inturri, Moshe Ben-Akiva
Summary: In most cities, the transit system consists of fixed-route transportation, which results in limited service quality for suburban areas and off-peak periods. However, completely replacing fixed-route with demand-responsive transit would be costly. Our proposal is a Continuous Approximation model that combines both fixed-route and demand-responsive transportation, allowing for adaptive transit planning. Numerical results show that this model significantly improves user-related cost and reduces access time to the main trunk service, particularly in suburbs. This model can guide the planning of future transit systems by integrating fixed and demand-responsive transportation.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Economics
Antonis F. Lentzakis, Ravi Seshadri, Moshe Ben-Akiva
Summary: Congestion pricing is a standard approach to mitigate traffic congestion. The advancement of satellite technology has led to the interest in distance-based congestion pricing schemes, which eliminate the need for fixed infrastructure. Distance-based pricing has the potential to effectively manage traffic congestion.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Economics
Duy Q. Nguyen-Phuoc, Meng Zhou, Ming Hong Chua, Andre Romano Alho, Simon Oh, Ravi Seshadri, Diem-Trinh Le
Summary: Several cities worldwide are adopting car-lite policies to reduce traffic congestion and urban pollution. This paper explores the impact of Automated Mobility-on-Demand (AMOD) on public transport (PT) using an agent-based microsimulation platform. The results show that the share of PT usage decreases significantly in the Partial Automation scenario, but increases in the Full Automation scenario. The findings have useful implications for urban and transport planners in implementing AMOD.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Transportation Science & Technology
Siyu Chen, Ravi Seshadri, Carlos Lima Azevedo, Arun P. Akkinepally, Renming Liu, Andrea Araldo, Yu Jiang, Moshe E. Ben-Akiva
Summary: Tradable mobility credit (TMC) schemes are an effective approach to mitigate urban traffic congestion and its adverse effects. This paper proposes and analyzes alternative market models for the TMC system, with a focus on market design aspects and individual behavior modeling. Simulation experiments have shown that small, fixed transaction fees can effectively reduce undesirable speculation in the market without significant efficiency loss. Continuous time allocation of credits and the adaptiveness of the market enhance the system's robustness in handling non-recurrent events and forecasting errors. The TMC scheme is more equitable and can achieve higher social welfare than congestion pricing when considering income effects.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Jeppe Rich, Ravi Seshadri, Ali Jamal Jomeh, Sofus Rasmus Clausen
Summary: This paper examines the potential of autonomous vehicle (AV) technology for enhancing first and last mile services for a light-rail station. The findings indicate that, for a high-frequency light-rail feeder system, fixed routing is the preferred option, but demand-responsive services can be as effective as fixed routing in off-peak hours. A combination of the two services could be beneficial in certain contexts. Urban sprawl has an impact on the performance of the system, with demand-responsive services becoming relatively better when urban sprawl increases, while fixed routing remains superior across most key-performance indicators. Cost-benefit analysis is employed to assess the performance of the different services.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Transportation Science & Technology
Takanori Sakai, Yusuke Hara, Ravi Seshadri, Andre Romano Alho, Md Sami Hasnine, Peiyu Jing, ZhiYuan Chua, Moshe Ben-Akiva
Summary: This article introduces a novel framework for predicting e-commerce demand and evaluating the impacts of relevant policies and solutions. The framework considers the impacts of delivery options and their attributes on multiple dimensions of e-commerce demand and simulates the changes in e-commerce demand.
TRANSPORTATION PLANNING AND TECHNOLOGY
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Antonis F. Lentzakis, Ravi Seshadri, Moshe Ben-Akiva
Summary: This study proposes using subspace clustering to define tolling zones and alter travelers' decision-making, showing positive impact in distance-based toll implementations.
2021 7TH INTERNATIONAL CONFERENCE ON MODELS AND TECHNOLOGIES FOR INTELLIGENT TRANSPORTATION SYSTEMS (MT-ITS)
(2021)
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)