Article
Transportation
Yuan Zhang, Qixiu Cheng, Yang Liu, Zhiyuan Liu
Summary: This study proposes an instance-based transfer learning method to tackle traffic flow estimation problem in urban transport networks. Case studies based on simulation data and empirical data demonstrate the effectiveness of the method. It outperforms existing methods by reducing the estimation error by two percentage points for road segments without detectors.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Xiaoling Luo, Xiaofeng Li, Mohammad Razaur Rahman Shaon, Yongxiang Zhang
Summary: This paper proposes a strategy for efficiently merging automated vehicles from a multiple-lane ramp. The proposed strategy outperforms traditional strategies in reducing delay and is found to be the most reliable in various scenarios.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Kam K. H. Ng
Summary: This study proposes a weather data-driven flight path planning method to reduce contrail production by rerouting flights in different atmospheric conditions. Historical data is used to generate spatial meteorological conditions, which are formulated as uncertain factors to develop a robust solution. Airlines can determine allowable flight level changes and optimize for lower contrail length and fuel consumption cost.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Yiting Hu, Xiling Luo, Dongmei Bai
Summary: This paper proposes a bi-level programming model to optimize the queueing network in airport access, which can alleviate queue congestion and improve passenger evacuation efficiency in airport public transport systems.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
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
Transportation
Qi Liu, Joseph Y. J. Chow
Summary: A network-level transit passenger flow estimation model based on congested schedule-based transit equilibrium assignment is proposed, using stop count data. The methodology is verified using synthetic data sets and bus data from Shanghai, showing good accuracy compared to other estimation methods.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Ziang Yao, Jan-Dirk Schmocker
Summary: The ease of access is crucial for the wider acceptance and adaptation of free-floating sharing services. This research quantifies the access distance by considering the density of travellers and bicycles, and examines the effects of different information-seeking and reservation strategies. The findings suggest that active seeking of bicycles does not necessarily improve system performance, enabling reservations can lead to longer travel times, and increasing bicycle supply or reservation rate may initially increase and then decrease reliability.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Yu Jiang, Zhenyu Liu, Zhitao Hu, Honghai Zhang, Cheng Xu
Summary: This paper proposes an integrated scheduling model (ISAA) to handle the complex problem of aircraft arrival scheduling. By incorporating various constraints into the model, the aim is to reduce passenger delay and swap cost. Various neighbourhood search algorithms and local search are used to solve the problem, and compared with the sequential method, the overall performance is significantly improved.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Chuanyao Li, Yichao Lu, Gege Jiang, Qijia Sun
Summary: This paper investigates the implementation of a staggered shifts scheme in a traffic congestion model. The results demonstrate that this scheme can reduce the total cost of transportation without changing the flow pattern of commuters.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Liangze Yang, Chi-Wang Shu, S. C. Wong, Mengping Zhang, Jie Du
Summary: This study investigates the existence and uniqueness of solutions to the Hoogendoorn-Bovy (HB) pedestrian flow model. The results show that the HB model can be transformed into a forward conservation law equation and a backward Hamilton-Jacobi equation, ensuring the existence and uniqueness of solutions for both equations when suitable parameters are chosen.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Jiali Peng, Shangguan Wei, Linguo Chai
Summary: This paper investigates the lane-changing behavior of heterogeneous traffic agents consisting of human-driven vehicles (HDVs) and connected-automated vehicles (CAVs). It proposes an optimization method for CAV lane changing under different penetration rates and examines the effectiveness of optimal control strategies through numerical simulations. The results show that these strategies improve the comfort, efficiency, safety, and stability of heterogeneous traffic agents compared to baseline maneuvers.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Mehmet Sirin Artan, Ismail Sahin
Summary: Deteriorations are considered during the design phase to maintain reliability. Tracking the response of periodic timetables to deteriorating events and settling delays within a reasonable time are desired outcomes.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Zheng Zhu, Meng Xu, Yining Di, Xiqun (Michael) Chen, Jingru Yu
Summary: In this study, a data-driven approach based on the additive Gaussian Process Model (AGPM) is proposed for ride-sourcing market modeling. The results demonstrate the advantages of AGPMs in terms of estimation accuracy and their ability to design and estimate idle vehicle relocation strategies.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Thomas Maxner, Andisheh Ranjbari, Chase P. Dowling, Seyma Guenes
Summary: Curbspace in urban areas is a limited resource where delivery, ridehailing, and passenger vehicles compete for space. Cities lack the necessary tools or data to make informed decisions about curb use allocations. This research analyzes and quantifies the impact of different curb use allocations on curb performance through simulation. It provides metrics to evaluate productivity, accessibility, and CO2 emissions, allowing municipalities to analyze and choose curb management strategies aligned with their policy goals.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Xinshao Zhang, Zhaocheng He, Yiting Zhu, Linlin You
Summary: Transit Signal Priority (TSP) strategy grants public transit vehicles the privilege to pass through intersections without stopping. Previous studies mainly focused on maximizing the utility of public transportation, which might compromise the efficiency of social vehicles. This paper introduces an Adaptive Transit Signal Priority (ATSP) model that considers the efficiency of both buses and social vehicles. It consists of a Single Request Adaptive Transit Signal Priority (SR-ATSP) module and a Multi-Request Adaptive Transit Signal Priority (MR-ATSP) module. Simulation experiments demonstrate that the proposed ATSP model achieves priority treatment for 45% of buses and reduces the waiting time of social vehicles by 12%, outperforming other commonly used TSP models in terms of reducing the waiting time of both buses and social vehicles.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Qiaozhen Zhu, Yun Bai, Lingling Yang, Yao Chen, Dongyang Yan
Summary: This paper proposes a collaborative model to optimize train rescue operations and timetable rescheduling. The model includes various strategies such as retiming, train cancellation, skip-stopping, and inserting additional trains. The objective is to minimize the duration of train rescue and the number of stranded passengers. The results show that the proposed method reduces the number of stranded passengers by 28.6% at a slight increase in train rescue duration compared to the sequential method. Moreover, inserting additional trains and skip-stopping are found to be effective in improving service quality during disruptions.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Wenzhang Yang, Changyin Dong, Hao Wang
Summary: In this study, an on-ramp cooperative control strategy for connected and automated vehicles (CAVs) based on the virtual platoon method is proposed. The formation rules of the virtual platoon and merging conditions of the vehicles are introduced. Different control strategies are arranged for different types of vehicle combinations in the virtual platoon. Merging speed control is proposed for vehicle combinations in different lanes. The simulation results show that merging speed control effectively increases vehicle speed and reduces fuel consumption and average pollutant emissions. In the typical macroscopic simulation, the average speed of vehicles with merging speed control increased by 25%, while fuel consumption and average pollutant emissions decreased by 31.4% and 52%. A longer communication area, shorter desired gap headway, and smaller flow rate can lead to higher vehicle speed, lower fuel consumption and pollutant emissions. Fuel consumption and pollutant emissions are inversely proportional to the steady speed.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Ren-Yong Guo, Hai-Jun Huang
Summary: This paper investigates the dynamic entry pedestrian flow assignment problem. The problem involves a scenario where pedestrians enter a public place with multiple entrances and internal obstacles and then proceed to their destinations. The objective is to determine the entrance, route, and destination choices of pedestrians in order to minimize their total entry time. A mesoscopic model is developed to describe the dynamic entry process and a heuristic algorithm is proposed to solve the problem. Numerical investigations are conducted to demonstrate the model's applications and the effectiveness of the algorithm, particularly for a larger number of entry pedestrians.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Ling Zhu, Shukai Li, Yuting Hu, Bin Jia
Summary: This paper investigates the robust collaborative train timetabling optimization problem by integrating short-turning strategy and train circulation plan while considering the uncertainty in passenger demand. The results show that the proposed strategy can better support the balance between stranded passengers and train utilization, and robust strategies perform well in the trade-off between the optimality and conservatism of the solutions.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Yu-Zhang Chen, Cong-Ling Shi, Christian G. Claudel, Mao-Bin Hu
Summary: This paper studies the problem of synchronizing the first train timetable with interval trains, considering both ordinary trains and interval trains. A mixed integer programming problem is formulated and a genetic simulated annealing algorithm is developed for the case study of the Beijing subway network. The proposed model and algorithm effectively improve the performance of the first train timetable synchronization, reducing the total transfer waiting time and the number of long waiting time transfer directions in the Beijing subway network. The results indicate that operating interval trains is an effective way to solve the problem of long waiting time in the early morning.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
