Transportation Research Part B-Methodological最新文献

{"title":"Modeling instantaneous queuing effects in the traffic assignment problem with consideration of demand fluctuations in the modeling period","authors":"Yuxin Shi ,&nbsp;William H.K. Lam ,&nbsp;Hao Fu ,&nbsp;H.W. Ho ,&nbsp;Mei Lam Tam ,&nbsp;Wei Ma","doi":"10.1016/j.trb.2025.103248","DOIUrl":"10.1016/j.trb.2025.103248","url":null,"abstract":"<div><div>Instantaneous traffic queues, introducing fluctuated queuing delays, significantly affect the journey times and route choices of travelers particularly during the peak hour periods in congested road networks. Distinguished from average residual queues in static traffic assignment problems, instantaneous queues form and dissipate within minuscule time frames of a modeling period, triggered by an inflow exceeding link capacity, owning to instantaneous demand fluctuations. The inclusion of instantaneous queuing effects is of paramount importance, given their more frequent occurrence compared to residual queues. However, little attention has been given to these instantaneous queuing effects in static traffic assignment models for strategic planning. To fill this gap, this paper proposes a novel instantaneous traffic assignment (ITA) model to incorporate instantaneous queuing effects in congested road networks, accounting for within-period demand fluctuations. The enhanced ITA modeling framework is proposed encompassing two fixed-point problems for network loading and a logit-based stochastic user equilibrium assignment model. The ITA model is formulated as an equivalent variational inequality problem. The mathematical properties of the proposed model such as the stability of the unique solutions can be rigorously proved. An improved method of successive weighted average algorithm with an adaptive step size is developed to solve the proposed model in order to facilitate the examination of instantaneous queuing effects in real-world contexts for large-scale networks. Numerical examples are conducted to demonstrate the merits and efficacy of the proposed ITA model. The feasibility and applicability of the proposed model in reality are further illustrated in case studies of three different road networks.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"197 ","pages":"Article 103248"},"PeriodicalIF":5.8,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Liner fleet deployment and slot allocation problem: A distributionally robust optimization model with joint chance constraints","authors":"Tao Zhang ,&nbsp;Shuaian Wang ,&nbsp;Xu Xin","doi":"10.1016/j.trb.2025.103236","DOIUrl":"10.1016/j.trb.2025.103236","url":null,"abstract":"<div><div>In this paper, we address the classical liner fleet deployment and slot allocation joint optimization problem in the maritime field with uncertain container transportation demand. We relax the assumption in existing studies that the demand distribution function is known because container transportation demand is deeply affected by the world’s economic and political landscape. With the help of advances in distributionally robust optimization theory, we develop a two-stage data-driven robust chance-constrained model. This distribution-free model requires only limited historical demand data as input and jointly optimizes the class (i.e., capacity) and number of liners assigned on each route and the scheme for allocating containers on each leg to maximize the profit (container transportation revenue minus fleet operating costs, voyage costs, and capital costs) of the liner company. The joint chance constraint in the model requires that the transportation demand of the contract shipper be satisfied with a pre-determined probability. We then reformulate the model as a second-order cone programming and design a customized algorithm to explore the global optimal solution based on the outer approximation algorithm framework. This paper can serve as a baseline distribution-free model for solving liner fleet deployment and slot allocation joint optimization problems.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"197 ","pages":"Article 103236"},"PeriodicalIF":5.8,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Post-disruption lane reversal optimization with surrogate modeling to improve urban traffic resilience","authors":"Qing-Long Lu ,&nbsp;Wenzhe Sun ,&nbsp;Cheng Lyu ,&nbsp;Jan-Dirk Schmöcker ,&nbsp;Constantinos Antoniou","doi":"10.1016/j.trb.2025.103237","DOIUrl":"10.1016/j.trb.2025.103237","url":null,"abstract":"<div><div>Rapid post-disruption recovery is essential but challenging, given the complex interactions between vehicular flows and the network supply. Simulation-based methods are widely used to assist the planner with realistic user-system interactions in the recovery measure optimization, though the application to large-scale transportation networks remains computationally expensive. This study explores the feasibility of using surrogate models as a time-efficient alternative to resource-intensive simulations. Lane reversal control is employed as a novel recovery measure and an optimization framework prioritizing systematic recovery is developed. A resilience loss indicator based on macroscopic fundamental diagram (MFD) dynamics is used to evaluate the real-time performance of the transportation system. The proposed surrogate model, therefore, also focuses on approximating recovery evaluation indicators, i.e., the resilience loss, other than link flows and density. The surrogate model contains a dynamic analytical network model and a Gaussian process regression (GPR) model. The former provides the analytical resilience loss and considers the temporal correlation of network changes resulting from time-dependent lane reversal decisions. The latter captures the difference between simulated and analytical resilience losses. Experiments are conducted on a large real-world road network in Kyoto City. The proposed approach demonstrates its efficacy by mitigating traffic resilience loss by about 6% under scenarios of 15 and 20 controllable links with a mere five algorithm iterations, requiring only 150 simulation runs. We also illustrate a trade-off between recovery performance and control resources that more controllable links unnecessarily offer better resilience improvement given the short decision-making duration and the very tight computational budget.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"197 ","pages":"Article 103237"},"PeriodicalIF":5.8,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143923404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel multi-objective evolutionary algorithm for transit network design and frequency-setting problem considering passengers’ choice behaviors under station congestion","authors":"Mingzhang Liang ,&nbsp;Min Xu ,&nbsp;Shuaian Wang","doi":"10.1016/j.trb.2025.103238","DOIUrl":"10.1016/j.trb.2025.103238","url":null,"abstract":"<div><div>The transit network design and frequency-setting problem (TNDFSP) plays a critical role in urban transit system planning. Due to the conflict between the level of service and operating costs, extensive research has been conducted to obtain a set of trade-off solutions between the interests of users and operators. However, most studies ignored the effects of station congestion in TNDFSP, resulting in unrealistic solutions or a failure to achieve optimal design schemes. Therefore, this study investigates the multi-objective optimization of TNDFSP considering users’ choice behaviors under station congestion. To address the problem, a multi-objective bilevel optimization model is first formulated. The upper level is a bi-objective optimization model with two conflicting objectives: minimizing users’ cost and minimizing operator’s cost. The lower-level problem is a passenger assignment problem under station congestion. Moreover, a novel multi-objective evolutionary algorithm based on objective space decomposition (MOEA-OSD) is proposed to solve the complex problem. When dealing with multi-objective optimizations, a decomposition mechanism is developed to convert the problem into multiple subproblems. These subproblems are optimized using an evolutionary approach with newly designed selection process and elite preservation strategy to achieve desirable convergence and diversity. The computational results obtained using Mandl’s benchmark demonstrate the efficacy of MOEA-OSD and the advantage of the proposed model in achieving more comprehensive trade-off solutions.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"197 ","pages":"Article 103238"},"PeriodicalIF":5.8,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online adaptive shockwave detection and inpainting based on vehicle trajectory data: rigorous algorithm design and theory development","authors":"Chenlu Pu,&nbsp;Lili Du","doi":"10.1016/j.trb.2025.103225","DOIUrl":"10.1016/j.trb.2025.103225","url":null,"abstract":"<div><div>Traffic shockwaves, as the boundary of distinct traffic states, capture the temporal-spatial characteristics of traffic fluctuation formation and propagation. Monitoring shockwaves facilitates real-time traffic management and control to improve traffic efficiency and safety. However, detecting shockwaves is challenging due to the complex nature of traffic dynamics and limited data collection. Existing methods either require prior knowledge of shockwaves to detect them in specific traffic scenarios or are capable of detecting only partial shockwaves with approximated propagation speed. To address these limitations, this study develops an e<u>F</u>fective online <u>S</u>hock<u>W</u>ave de<u>T</u>ection and <u>I</u>npainting approach using vehicle trajectory data (labeled as SWIFT) collected in broad traffic scenarios. Briefly, first noticing the correlation between turning points for piecewise linear regression and breakpoints on each individual trajectory curve where a vehicle experiences significant speed changes, we develop a novel automatic breakpoint identification method by renovating the piecewise linear regression with shockwave features’ constraint. Next, we design an adaptive data-driven online shockwave detection approach that operates without any prior knowledge of shockwaves. This approach sequentially classifies and connects breakpoints based on shockwave propagation characteristics to generate distinct piecewise linear shape shockwave traces with mathematically guaranteed error bounds. Considering the shockwaves detected from data-driven approaches are usually incomplete, we establish the theoretical foundation including critical definitions, corollaries, and a theorem to guide shockwave inpainting and missing shockwave revealing based on the geometry representation of shockwave features. Built upon that, we develop a generative algorithm that verifies shockwave endpoints one by one based on partial trajectory data to repair incomplete shockwaves and reveal missing shockwaves. The numerical experiments using the NGSIM dataset demonstrated the accuracy, adaptiveness, and robustness of the SWIFT under various data collection settings (e.g., penetration rates, detection window sizes, sampling intervals) and different traffic scenarios.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"197 ","pages":"Article 103225"},"PeriodicalIF":5.8,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Capacity drop at active bottlenecks: An empirical study based on trajectory data","authors":"Yu Han ,&nbsp;Jiarui Wu ,&nbsp;Fan Ding ,&nbsp;Zhibin Li ,&nbsp;Pan Liu ,&nbsp;Ludovic Leclercq","doi":"10.1016/j.trb.2025.103218","DOIUrl":"10.1016/j.trb.2025.103218","url":null,"abstract":"<div><div>Capacity drop, a traffic phenomenon indicating that the discharge flow from a queue is lower than the pre-queue flow, is commonly observed at freeway bottlenecks. In the literature, the majority of empirical studies on capacity drop rely on aggregated traffic flow data. To fully understand the mechanism behind capacity drop, it is essential to analyze trajectory data, which captures the microscopic behavior of individual vehicles. However, the availability of high-quality trajectory data covering both sufficient spatial and temporal scope is limited. Consequently, existing theories and mechanisms to explain capacity drop from the perspective of vehicle behavior are predominantly analytical, lacking direct evidence to validate their impacts on contributing to capacity drop. This paper fills this gap by conducting a comprehensive empirical analysis of capacity drop using high-resolution trajectory data extracted from videos recorded by unmanned aerial vehicles. The empirical analysis examines the relative effects of various capacity drop mechanisms and reveals the following findings: (i) The late responses of hesitant vehicles during the acceleration process significantly contribute to capacity drop; (ii) the impact of response delay on queue discharge rate is more pronounced at lower congestion speeds; (iii) response delays primarily result from deceleration during car-following, followed by lane changes, with their combined effect having a more pronounced triggering impact. These findings are subsequently validated using data collected from another site. The findings presented in this paper are valuable for developing more accurate microscopic traffic simulation models and designing more effective traffic management and control strategies.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"196 ","pages":"Article 103218"},"PeriodicalIF":5.8,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploiting modularity for co-modal passenger-freight transportation","authors":"Hongyu Zheng ,&nbsp;Jiayang Li ,&nbsp;Jane Lin ,&nbsp;Yu (Marco) Nie","doi":"10.1016/j.trb.2025.103217","DOIUrl":"10.1016/j.trb.2025.103217","url":null,"abstract":"<div><div>Using a game theoretic approach, this paper explores a futuristic passenger-freight co-modality system that leverages autonomous modular vehicle (AMV) technology. In our model, a transit operator and a freight carrier operate within a stylized city, transporting passengers and parcels, respectively. The freight carrier can rent the transit operator’s underutilized transport capacity during off-peak periods through a market mechanism. By analyzing the design problems of both the operator and the carrier, we characterize their willingness-to-trade function, which defines the feasible region for a two-player game. We formulate four distinct market mechanisms, each corresponding to a different type of game. The first two are leader–follower Stackelberg games, differing in which player assumes the leadership role. The third mechanism features iterative negotiation between both players until equilibrium is achieved, while the fourth assumes full cooperation. Our results indicate that in the Stackelberg games, the leader captures all the benefits of co-modality, whereas neither player benefits in the negotiation game. Moreover, the carrier-led Stackelberg game proves more efficient than the operator-led one. Finally, while regulatory interventions such as price caps can promote a more equitable benefit distribution in the Stackelberg framework, similar outcomes are attainable without intervention in the cooperative game.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"196 ","pages":"Article 103217"},"PeriodicalIF":5.8,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Airport charge, terminal capacity, and suggested airport arrival time: Considering non-aeronautical business","authors":"Yue Huai ,&nbsp;Enoch Lee ,&nbsp;Hong K. Lo ,&nbsp;Anming Zhang","doi":"10.1016/j.trb.2025.103222","DOIUrl":"10.1016/j.trb.2025.103222","url":null,"abstract":"<div><div>This study investigates the optimal decisions of airports regarding charges, capacity, and passengers’ suggested arrival time at the airport (before flight departures) under different objectives (maximizing airport profit or social welfare). Our model incorporates an airport, airlines with market power, and passengers, and examines the impact on concession revenue of dwell time in (terminal) retail zones and queuing time in check-in zones. We find that whether a profit-maximizing airport charges or subsidizes airlines for using its aeronautical service depends critically on whether the trip demand is elastic with respect to airport charge and whether trip demand increases the concession surplus. In particular, when this is elastic and the trip demand also raises concession revenue, the airport will <em>subsidize</em> airlines. For welfare-maximizing airports, when trip demand decreases the concession surplus (due to shopping time shrinkage), airports would set the charge that the ticket price paid by passengers is higher than the social marginal cost incurred. Further, the airport’s decisions regarding terminal capacity are influenced by the trade-off between the revenue gained from increased traffic and the revenue lost from the reduced dwell time. By comparison with a welfare-maximizing airport, a profit-maximizing airport tends to invest more in terminal capacity under lower traffic, but less under higher traffic: basically, the effect of expanding terminal capacity on increasing shopping time (dwell time in the retail zone) is more pronounced for lower traffic, and the effect diminishes for higher traffic. The study also shows that a profit-maximizing airport would suggest travelers arrive at the airport earlier than a welfare-maximizing airport, so as to increase the non-aeronautical revenue.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"196 ","pages":"Article 103222"},"PeriodicalIF":5.8,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A risk-averse two-stage stochastic programming approach for backup rolling stock allocation and metro train rescheduling under uncertain disturbances","authors":"Boyi Su ,&nbsp;Andrea D’Ariano ,&nbsp;Shuai Su ,&nbsp;Zhikai Wang ,&nbsp;Marta Leonina Tessitore ,&nbsp;Tao Tang","doi":"10.1016/j.trb.2025.103233","DOIUrl":"10.1016/j.trb.2025.103233","url":null,"abstract":"<div><div>Disturbances occur inevitably during daily operations of the metro system, leading to train delays and low service quality. Different from common deterministic reactive train rescheduling frameworks, taking the inherent uncertain characteristic of disturbance into account, this paper formulates a two-stage stochastic programming model to address the integration of proactive backup rolling stock allocation and reactive train rescheduling. Specifically, the backup rolling stock allocation plan is optimized in the first stage, while the train timetable and rolling stock circulation are rescheduled under different disturbance realizations in the second stage. The objective is to achieve a balance between allocation costs and negative disturbance impacts, which is evaluated by the mean-conditional value-at-risk criterion on account of the risk-averse attitude of train dispatchers. For computational tractability, the proposed model is reformulated as an equivalent mixed-integer linear programming (MILP) model. To improve computational efficiency, an innovative solution framework is designed. The integer L-shaped method is used to decompose the MILP into a master problem and a series of subproblems, with three acceleration techniques introduced to expedite the subproblem-solving process. Finally, numerical experiments are carried out based on the Beijing Batong Metro Line to verify the performance of the proposed mathematical model and solution framework. The results indicate that the proposed method outperforms benchmarks. Furthermore, comprehensive analysis is conducted on the effects of different parameter settings to provide some managerial insights for dispatchers.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"196 ","pages":"Article 103233"},"PeriodicalIF":5.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Column-and-row generation based exact algorithm for relay-based on-demand delivery systems","authors":"Xueting He,&nbsp;Lu Zhen","doi":"10.1016/j.trb.2025.103223","DOIUrl":"10.1016/j.trb.2025.103223","url":null,"abstract":"<div><div>This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport it to another station and then another courier will transport it to its final destination. Using mixed-integer linear programing, this paper formulates a novel arc-based set-packing model with two types of columns, i.e., drone plans and courier plans, to maximize the profit from transporting a batch of orders. By combining branch-and-price, column-and-row generation, and some tailored acceleration tactics, an exact algorithm is designed and implemented to efficiently solve the model. Experimental results validate the efficiency of the proposed exact algorithm. Moreover, we find that large numbers of couriers, drones, or stations do not always substantially improve the system’s performance; if order due times are urgent, the benefit of drones (couriers) is more (less) significant. The model’s robustness and the applicability of our methodology in large-scale applications are validated.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"196 ","pages":"Article 103223"},"PeriodicalIF":5.8,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}