Article
Management
Christof Defryn, Julian Arthur Pawel Golak, Alexander Grigoriev, Veerle Timmermans
Summary: This study focuses on minimizing the aggregated fuel consumption by vessels in an inland waterway, considering the impact of different velocities on fuel consumption and the existence of Nash equilibrium. A mechanism involving payments between vessels is proposed to ensure Nash equilibrium while reducing fuel consumption.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Wenjia Wei, Kaiping Xue, Jiangping Han, Yitao Xing, David S. L. Wei, Peilin Hong
Summary: This paper proposes a BBR-based congestion control and packet scheduling scheme BCCPS to improve the performance of MPTCP in heterogeneous wireless networks. It adaptively adjusts the sending rate and introduces fine-grained packet scheduling to enhance throughput and reduce application layer completion time.Experimental results demonstrate that the proposed scheme significantly outperforms existing MPTCP schemes in heterogeneous wireless environments.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Environmental Studies
Yanyan Ding, Xinwei Li, Sisi Jian
Summary: V2G technology allows EVs to discharge unused power to the grid, serving as flexible energy resources. This study investigates the interaction between transport and power systems during peak periods with V2G. Commuters choosing to discharge can earn rewards but also face delay costs.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Economics
Tingting Zhu, Yao Li, Jiancheng Long
Summary: This paper develops a bottleneck model with continuous scheduling preference (CSP) and analyzes the departure time choice equilibrium of commuters. The study finds that considering CSP can eliminate the discontinuity of the departure rate curve and provide more accurate estimates of commuters' bottleneck queuing time and total system travel cost.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Engineering, Civil
Zemian Ke, Zhibin Li, Zehong Cao, Pan Liu
Summary: The study evaluates the performance of transfer learning algorithm in deep reinforcement learning-based VSL control, showing successful transfer of knowledge from source to target scenarios, shortening training process and improving control effects.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Civil
Zhuo Chen, Xiaoyue Cathy Liu
Summary: This study proposes a new travel time reliability measurement for identifying freeway bottlenecks with high probability. By using statistical distance measurements, it can effectively identify both recurrent and non-recurrent bottlenecks, as demonstrated in a case study on the I-15 freeway corridor in Salt Lake City. The recurrent bottlenecks show clustering characteristics, while locations with high probability of non-recurrent bottlenecks scatter spatially and temporally, aligning with the random nature of non-recurrent congestion.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Computer Science, Hardware & Architecture
Enhuan Dong, Peng Gao, Yuan Yang, Mingwei Xu, Xiaoming Fu, Jiahai Yang
Summary: This paper introduces a data-driven method, SmartSBD, for intelligent detection of shared bottlenecks in MPTCP. By collecting system logs, extracting features, and training a classifier, SmartSBD can accurately detect whether MPTCP subflows share the same bottleneck. Experimental results demonstrate that SmartSBD outperforms existing approaches.
Article
Management
Song-Hee Kim, Fanyin Zheng, Joan Brown
Summary: This study empirically examines the congestion spillover effect in a hospital with 16 inpatient units. The results show that congestion propagation is significant and substantial, with a 10% increase in one unit's utilization leading to a 4.33% increase in its neighboring unit's utilization. Counterfactual analyses reveal that adding one bed to the bottleneck unit can free up 4.14 beds in the hospital, resulting in increased hospital visits and improved throughput.
MANAGEMENT SCIENCE
(2023)
Article
Computer Science, Information Systems
Jin Ye, Lin Li, Zihan Chen, Guihao Chen, Sen Liu, Jiawei Huang, Jianxin Wang, Tian He
Summary: This paper proposes a lightweight yet accurate approach to detect shared bottleneck of multiple subflows. By utilizing the widely deployed ECN scheme to capture the real congestion state of shared bottlenecks, this method is compatible with various MPTCP congestion control algorithms and achieves a high detection accuracy in experiments.
COMPUTER COMMUNICATIONS
(2022)
Article
Operations Research & Management Science
Raphaeel Lamotte, Andre de Palma, Nikolas Geroliminis
Summary: Research shows that metering-based priority schemes can result in significant cost savings and Pareto improvement, but the effects vary with sources of heterogeneity. Randomly allocated priority scheme's relative cost savings decrease with flexibility heterogeneity, while HOV-MBP scheme achieves better benefit distribution through ordering effect and modal shift.
TRANSPORTATION SCIENCE
(2022)
Article
Computer Science, Information Systems
Charles Kihungi Njogu, Wang Yang, Humphrey Waita Njogu, Adrian Bosire
Summary: The Google research team developed a new TCP congestion control algorithm called BBR, which maximizes delivery rate and minimizes round-trip time to improve bandwidth utilization and performance. However, BBR has fairness issues, favoring long RTT flows and causing high retransmission rates and queuing delay. To address this, the BBR-EFRA algorithm was proposed, which adaptively controls the congestion window and ensures fair competition for available bandwidth among different RTT flows.
COMPUTER COMMUNICATIONS
(2023)
Article
Mathematics
Chuanyao Li, Yichao Lu, Yuqiang Wang, Gege Jiang
Summary: This paper examines the morning commute problem in the bottleneck model using exponential scheduling preference (ESP), and analytically derives solutions and economic properties of user equilibrium and social optimum. The results show that ESP eliminates discontinuity and non-differentiability in the commute process, and emphasizes the importance of considering ESP in analyzing travel behavior and policy-making.
ELECTRONIC RESEARCH ARCHIVE
(2022)
Article
Economics
Xiaojuan Yu, Vincent A. C. van den Berg, Zhi-Chun Li
Summary: In the face of capacity disruptions, information provision and congestion pricing are effective policies. This study compares responsive pricing with habitual pricing under perfect and imperfect information. The findings suggest that the two tolls become more similar when the information quality is imperfect or uncertainty is lower. Despite the potential benefits of responsive pricing, the differences in effects between the two tolls are generally small. Therefore, considering the potential unpopularity and high implementation costs of responsive pricing, the quality of information and the level of uncertainty play a significant role in road management decisions.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Oceanography
Tingsong Wang, Tianlu Li
Summary: This paper addresses a management problem of ship lock and formulates it as an activity-based bottleneck model. It discusses the selection and decision of ship's departure time, and proposes a dynamic toll scheme for ships to reduce waiting costs at ship lock.
OCEAN & COASTAL MANAGEMENT
(2022)
Article
Economics
Yao Deng, Dian Sheng, Baoli Liu
Summary: This paper introduces a bottleneck model to manage ship lock congestion, explores different congestion tolling and administrative schemes, and finds that MST can effectively substitute tolling schemes in most cases, even outperforming them under certain conditions. Combining MST with tolling schemes can increase efficiency, but caution should be taken when the benefits of MST are marginal or zero in certain cases.
Article
Economics
Yu Xiao, Nicolas Coulombel, Andre de Palma
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2017)
Article
Green & Sustainable Science & Technology
Biao Yin, Liu Liu, Nicolas Coulombel, Vincent Viguie
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Environmental Studies
Nicolas Coulombel, Laetitia Dablanc, Mathieu Gardrat, Martin Koning
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2018)
Article
Demography
Nicolas Coulombel, Andre de Palma
MATHEMATICAL POPULATION STUDIES
(2014)
Article
Economics
Vincent Benezech, Nicolas Coulombel
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2013)
Article
Environmental Studies
N. Coulombel, V. Boutueil, L. Liu, V. Viguie, B. Yin
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2019)
Article
Operations Research & Management Science
Sabina Buczkowska, Nicolas Coulombel, Matthieu de Lapparent
NETWORKS & SPATIAL ECONOMICS
(2019)
Article
Engineering, Civil
Biao Yin, Azise Oumar Diallo, Tatiana Seregina, Nicolas Coulombel, Liu Liu
Summary: This paper investigates the socio-economic impacts of the driving restriction zone policy for the Paris region, using the multi-agent transport simulation MATSim. The study evaluates two policy scenarios and finds that a larger-scale policy scenario leads to a greater modal shift from cars to public transport, resulting in a larger reduction in traffic emissions. However, both scenarios result in an increase in social cost. The findings suggest a trade-off between reducing emissions and increasing user costs, with the larger-scale policy scenario being more efficient.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Economics
Nicolas Coulombel, Emmanuel Munch, Cyril Pivano
Summary: This study investigates the congestion relief potential of staggered work hours (SWH) schemes for public transit. A framework combining a hybrid assignment model with a travel demand management module is developed to simulate the impact of SWH schemes on travel demand and public transit congestion. The findings suggest that SWH schemes can effectively alleviate congestion, but the benefits are moderate and come with substantial rescheduling costs. The study also provides insights for policy design, recommending the focus on shifting a small number of users by a large amount of time rather than a large number of users by a small amount of time.
Article
Engineering, Civil
Felix Carreyre, Tarek Chouaki, Nicolas Coulombel, Jaafar Berrada, Laurent Bouillaut, Sebastian Horl
Summary: The technological development of autonomous vehicles poses economic challenges. Through cost-benefit analysis of AV services, it was found that introducing AVs in dense urban environments would increase pressure on the road network and result in longer travel times for private car users, leading to consumer surplus loss that cannot compensate for the benefits of new AV users.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Civil
Mwendwa Kiko, Nicolas Coulombel, Alexis Poulhes, Tatiana Seregina, Guillaume Tremblin
Summary: This paper investigates the rebound effect of teleworking on commuting distance and time, considering behavioral changes among transport users. The study finds that the overall rebound effect is substantial, canceling out a significant portion of the gains in travel distance and time savings. However, the social benefits of teleworking remain significant, suggesting its potential contribution to reducing travel demand.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Economics
Nicolas Coulombel
Article
Transportation
Nicolas Coulombel
JOURNAL OF TRANSPORT AND LAND USE
(2017)
Article
Environmental Studies
A. Berry, Y. Jouffe, N. Coulombel, C. Guivarch
ENERGY RESEARCH & SOCIAL SCIENCE
(2016)
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)