Transportation Research Part B-Methodological最新文献

{"title":"Estimating gap acceptance parameters with a Bayesian approach","authors":"Samson Ting, Thomas Lymburn, Thomas Stemler, Yuchao Sun, Michael Small","doi":"10.1016/j.trb.2025.103157","DOIUrl":"https://doi.org/10.1016/j.trb.2025.103157","url":null,"abstract":"The gap acceptance framework is the theoretical basis for modelling traffic flow at intersections with a priority control. Reliable estimation methods for key gap acceptance parameters are important to more accurately predict key traffic performance measures such as capacity and delay. A notable challenge is that the critical gaps are not directly observable. Currently, the maximum likelihood estimator (MLE) is widely accepted as the most reliable method. In this research, we considered a Bayesian approach as an alternative framework for estimating gap acceptance parameters, which achieves a comparable performance to the MLE. We first formalised the gap acceptance statistical model and the estimand of interest, based on a Bayesian hierarchical formulation that naturally captures the variations between drivers. We then tested the performance of each method on simulated dataset, with the Bayesian posterior obtained through the No-U-Turn sampler, an adaptive Markov chain Monte Carlo algorithm. We showed that the MLE and the posterior mean as a point summary of the full posterior distribution have comparable performance, and both generally achieve a mean absolute error <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mrow><mml:mo>≤</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:math> s for different major stream flow <mml:math altimg=\"si314.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>q</mml:mi></mml:mrow><mml:mrow><mml:mi>p</mml:mi></mml:mrow></mml:msub></mml:math> in our experiment setup. In addition, we found that the standard error is higher for both low and high <mml:math altimg=\"si314.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>q</mml:mi></mml:mrow><mml:mrow><mml:mi>p</mml:mi></mml:mrow></mml:msub></mml:math> so any point estimator is unlikely to be equally reliable across all level of <mml:math altimg=\"si314.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>q</mml:mi></mml:mrow><mml:mrow><mml:mi>p</mml:mi></mml:mrow></mml:msub></mml:math>’s. Furthermore, we also identified a potential issue when assuming consistent drivers and log-normally distributed critical gaps at high <mml:math altimg=\"si314.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>q</mml:mi></mml:mrow><mml:mrow><mml:mi>p</mml:mi></mml:mrow></mml:msub></mml:math>, as the heavy tail of the log-normal can result in unrealistic dataset. The full Bayesian approach also allows inherent uncertainty quantification, which we found to be well-calibrated, in the sense that the credible intervals obtained have roughly the correct frequentist coverage as per confidence intervals constructed with frequentist methods. From a traffic engineering point of view, quantifying uncertainties in gap acceptance parameters, whether using Bayesian or frequentist methods, is important as they induce uncertainties on intersection performance metrics such as capacity and delay, which will allow more informed decision-making for infrastructure investment. In additio","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"18 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072519","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":"Modeling the residual queue and queue-dependent capacity in a static traffic assignment problem","authors":"Hao Fu, William H.K. Lam, Wei Ma, Yuxin Shi, Rui Jiang, Huijun Sun, Ziyou Gao","doi":"10.1016/j.trb.2025.103158","DOIUrl":"https://doi.org/10.1016/j.trb.2025.103158","url":null,"abstract":"The residual queue during a given study period (e.g., peak hour) is an important feature that should be considered when solving a traffic assignment problem under equilibrium for strategic traffic planning. Although studies have focused extensively on static or quasi-dynamic traffic assignment models considering the residual queue, they have failed to capture the situation wherein the equilibrium link flow passing through the link is less than the link physical capacity under congested conditions. To address this critical issue, we introduce a novel static traffic assignment model that explicitly incorporates the residual queue and queue-dependent link capacity. The proposed model ensures that equilibrium link flows remain within the physical capacity bounds, yielding estimations more aligned with data observed by traffic detectors, especially in oversaturated scenarios. A generalized link cost function considering queue-dependent capacity, with an additional queuing delay term is proposed. The queuing delay term represents the added travel cost under congestion, offering a framework wherein conventional static models, both with and without physical capacity constraints, become special cases of our model. Our study rigorously analyzes the mathematical properties of the new model, establishing the theoretical uniqueness of solutions for link flow and residual queue under certain conditions. We also introduce a gradient projection-based alternating minimization algorithm tailored for the proposed model. Numerical examples are conducted to demonstrate the superiority and merit of the proposed model and solution algorithm.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"24 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072517","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":"What do walking and e-hailing bring to scale economies in on-demand mobility?","authors":"Kenan Zhang, Javier Alonso-Mora, Andres Fielbaum","doi":"10.1016/j.trb.2025.103156","DOIUrl":"https://doi.org/10.1016/j.trb.2025.103156","url":null,"abstract":"This study investigates the impact of walking and e-hailing on the scale economies of on-demand mobility services. An analytical framework is developed to i) explicitly characterize the physical interactions between passengers and vehicles in the matching and pickup processes, and ii) derive the closed-form degree of scale economies (DSE) to quantify scale economies. The general model is then specified for conventional street-hailing and e-hailing, with and without walking before pickup and after dropoff. We show that, under a system-optimum fleet size, the market always exhibits economies of scale regardless of the matching mechanism and the walking behaviors, though the scale effect diminishes as passenger demand increases. Yet, street-hailing and e-hailing show different scale economies in their matching process. While street-hailing matching shows a constant DSE of two, e-hailing matching is more sensitive to demand and its DSE diminishes to one when passenger competition emerges. Walking, on the other hand, has mixed effects on the scale economies: while the reduced pickup and in-vehicle times bring a positive scale effect, the extra walking time and possible concentration of vacant vehicles and waiting passengers on streets negatively affect scale economies. All these analytical results are validated through agent-based simulations on Manhattan with real-life demand patterns.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"1 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072638","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":"Unveiling network capacity potential with imminent supply information part II: Backpressure-based validation","authors":"Dianchao Lin, Li Li","doi":"10.1016/j.trb.2025.103153","DOIUrl":"https://doi.org/10.1016/j.trb.2025.103153","url":null,"abstract":"The capacity region (CR) is a key index to characterize a dynamic processing system’s ability to handle incoming demands. It is a multidimensional space when the system has multiple origin–destination pairs where their service rates interact. An urban traffic network is such a system. Traffic congestion appears when its demand approaches or exceeds the upper frontier of its CR. Part I of this study theoretically proved that (1) accurate I-SFR information of additional conflicting movements can enlarge the CR, and (2) improving the I-SFR prediction accuracy of observed movements can expand the CR. However, such expansion has not been validated through experiments. Part II of this study thus focuses on validating the theoretical findings in Part I. We use a real-time traffic control policy, named BackPressure (BP) control, to act as a ruler to measure the size of CR. We first prove that BP policy with partial I-SFR information can stabilize the network within the corresponding CR. Then we design various calibrated simulation experiments to check the validity of the two findings in Part I. Specifically, we use reserve demand, which represents the distance between a given demand and the frontier of CR, as a direct index to reflect the size of CR, and use delay as an indirect index to reflect the changes in CR. Simulation results confirm the theories in Part I.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"97 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143072643","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":"Equilibrium horizontal queues and a paradox of tolling","authors":"Lewis J. Lehe, Ayush Pandey","doi":"10.1016/j.trb.2025.103152","DOIUrl":"https://doi.org/10.1016/j.trb.2025.103152","url":null,"abstract":"This paper shows that, in a static traffic model with elastic demand, increasing a toll may raise the equilibrium trip rate through a network. The result is obtained in models with horizontal queues and rules about merges and diverges assumed in the Cell Transmission Model for Network Traffic. The paper looks at three networks: (i) a road with a fixed bottleneck at the end; (ii) a road with a “triggerneck” diverge; and (iii) a ring road with two on-ramps and two off-ramps. In the triggerneck network, a toll increase may raise the total trip rate when traffic using an exit with bottleneck has a lower value of travel time savings than traffic bypassing the bottleneck. In the ring road, a toll increase may raise the total trip rate when the initial equilibrium is hypercongested. The derivations use an extensible “recipe” for analysis of networks with horizontal queues. Many diagrams and numerical examples are provided to illustrate.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"34 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027374","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":"Optimizing carbon emissions in green logistics for time-dependent routing","authors":"Yiming Liu, Yang Yu, Roberto Baldacci, Jiafu Tang, Wei Sun","doi":"10.1016/j.trb.2025.103155","DOIUrl":"https://doi.org/10.1016/j.trb.2025.103155","url":null,"abstract":"This paper considers a green vehicle routing problem termed the time-dependent green vehicle routing problem with time windows (TDGVRPTW). The TDGVRPTW is an extension of the green vehicle routing problem with time windows in green logistics. It considers time-dependent vehicle speed and aims to minimize carbon emissions. Since the travel times and carbon emissions between locations depend on the departure time from the starting location, optimizing carbon emissions requires determining the optimal departure times from the depot and customers. This paper presents a branch-price-and-cut (BPC) algorithm to solve the TDGVRPTW. The problem is formulated based on a set-partitioning model. To solve the pricing problem associated with the set-partitioning model, we first define backward non-dominated time-dependent arcs and optimal timed routes. We also introduce three types of routes, forward, backward, and patchwork optimal timed routes, and analyze their characteristics. Then, we introduce a method to adjust the times in backward and patchwork optimal timed routes from the latest to the earliest. We prove that this method guarantees correctness and effectively reduces complexity. We propose a bidirectional labeling algorithm to generate routes. The pricing problem employs state-of-the-art techniques, including limited memory subset row cuts (lm-SRCs), ng-route relaxation, and bucket graphs to enhance the algorithm’s efficiency. The BPC algorithm is tested on a set of instances derived from benchmark cases in the literature. Its various components and pricing strategies are evaluated, and its performance is compared with other algorithms from the literature. The results confirm the effectiveness of the proposed algorithm and its newly designed components in solving the TDGVRPTW.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"13 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027373","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":"Real-time policy for yard allocation of transshipment containers in a terminal","authors":"Abdo Abouelrous, Rommert Dekker, Laurens Bliek, Yingqian Zhang","doi":"10.1016/j.trb.2024.103138","DOIUrl":"https://doi.org/10.1016/j.trb.2024.103138","url":null,"abstract":"In this article, we investigate the problem of allocating storage space in a container terminal’s yard to transshipment containers. The main decision here concerns the block to which a container is assigned for storage until it is loaded later by another vessel. We propose a setting where some target performance measures are imposed on the discharge operations. In turn, the allocation decisions are made so as to reduce driving time from the storage blocks to the berth locations of the vessels that will pick up the containers. The trick here is to find an appropriate trade-off between the times spent on discharge and loading so that neither are delayed significantly. Using results from renewal theory, queuing theory and machine learning, we are able to quantify the effect of our allocation decisions on quay crane productivity. Thereafter, we formulate a mathematical optimization problem for the yard-allocation of containers and apply a meta-heuristic to solve it. Our method was developed for deployment by a software consultancy company for container terminals. We test our method using a real-time simulation and compare it with a benchmark from the literature. We show that our method generates reductions in vessel berth times and provide an overview on its economic impact.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"5 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989516","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":"Investment and financing of roadway digital infrastructure for automated driving","authors":"Amir Ahmadian, Sina Bahrami, Mehdi Nourinejad, Yafeng Yin","doi":"10.1016/j.trb.2024.103146","DOIUrl":"https://doi.org/10.1016/j.trb.2024.103146","url":null,"abstract":"Connected automated vehicles (CAVs) are equipped with sensors, enabling them to scan and analyze their surrounding environment. This capability empowers CAVs to make informed and efficient decisions regarding their motion; however, the limited spatial range and resolution of these sensors present challenges for achieving full autonomy. Cooperative sensing through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications offers an alternative approach to enrich CAVs’ environmental understanding. This study explores the optimal investment policy for vehicular connectivity and road-side sensor deployment under varying traffic flow conditions. It also extends the self-financing theorem to the sensor equipped roads and investigates whether an optimal toll can cover both the construction costs and the costs of equipping roads with sensing components. The stylized model of CAV mobility considers the interplay between stationary sensors installed road-side as a part of the infrastructure and mobile sensors of CAVs. Results indicate that under constrained budgets and low traffic flow, investing in infrastructure improvement is preferred. However, as traffic flow increases, prioritizing connectivity and data sharing among CAVs becomes more lucrative. Notably, in high traffic flow, a shift back to investing in stationary sensors may occur, depending on system settings. The findings provide insights into budget allocation to enhance CAV performance, advancing the development of efficient and safe automated driving systems. The analyses on the self-financing theorem also show that the optimal user tolls do not cover the cost of constructing digital infrastructure. However, if social planners consider the safety benefits of sensor equipped roads, the construction of digital infrastructure can be covered by the optimal user tolls. In addition, the revenue from optimal user tolls can cover the cost of equipping existing roads with sensors if their flow-capacity ratio is greater than a certain threshold.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"20 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142918064","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":"Shore-power capacity allocation in a container shipping network under ships’ strategic behaviors","authors":"Zhijia Tan, Dian Sheng, Yafeng Yin","doi":"10.1016/j.trb.2024.103151","DOIUrl":"https://doi.org/10.1016/j.trb.2024.103151","url":null,"abstract":"Shore power (SP) is an effective way to cut carbon emissions at ports by replacing fuel oil for docked ships. The adoption of SP by ships hinges on the onboard transformer setup cost and the cost saving from SP utilization in comparison with fuel oil. The allocation of SP capacity at ports influences the availability of SP-equipped berths and, along with conventional berths, incurs potential service delays. Misallocation can actually increase port emissions. This paper addresses the SP capacity allocation problem in a general container shipping network with multiple ports and a ship fleet. The service congestion or capacity-dependent waiting time at berths is considered, which results in strategic choices or choice equilibrium of ships on SP adoption. The emission quantity at each port is affected by the choice equilibrium of ships. For the benchmark case with a single port, we analytically identify a threshold SP capacity above which emissions decrease, below which a counterintuitive increase occurs. For the general shipping network, assuming government covers transformer setup costs, we develop an exact method to determine the critical level for each port to ensure emission reductions. A case study based on the Yangtze River is conducted to illustrate the analytical results.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"128 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142918066","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":"Solving the equity-aware dial-a-ride problem using an exact branch-cut-and-price algorithm","authors":"Shuocheng Guo, Iman Dayarian, Jian Li, Xinwu Qian","doi":"10.1016/j.trb.2024.103149","DOIUrl":"https://doi.org/10.1016/j.trb.2024.103149","url":null,"abstract":"This paper proposes a Branch-Cut-and-Price (BCP) algorithm to solve an equitable variant of the Dial-a-Ride problem (DARP), namely Equity-Aware DARP (EDARP), a bi-objective optimization problem that simultaneously minimizes the total routing cost and maximizes the Equity-of-Travel (EoT) outcomes for individual passengers. For passengers, EoT is specified as their detour rate, measured by the ratio between total in-vehicle time and door-to-door direct trip time. The EoT objective of EDARP is to minimize the maximum detour rate among all passengers while satisfying the DARP constraints. We model the EDARP using a min–max trip-based formulation, which is solved exactly using a tailored BCP algorithm. The BCP algorithm adopts the Column Generation method by decomposing the problem into a master problem and a subproblem. The subproblem is an Elementary Shortest Path Problem with Resource Constraints and Min–Max EoT (ESPPRC-MME), which is NP-hard. To efficiently solve the ESPPRC-MME, we develop a minimal-ride-time calibration algorithm and establish families of resource extension functions in compliance with equity-related resources. We also extend the applicability of EDARP to the operation of the dial-a-ride service during the pandemic aiming to minimize the maximum exposure risk of individual travelers. The effectiveness of our models and algorithms are comprehensively evaluated using both classic DARP instances as well as EDARP instances generated from real-world paratransit trip datasets. Computational results show that our BCP algorithm can optimally solve 50 out of 54 real-world instances (up to 55 passengers and 13 vehicles covering 110 nodes) within a time limit of one hour. Important practical insights are also discussed by investigating the Pareto front and the Lorenz curves for trip inequity based on the optimal outcomes of real-world instances.","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"308 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142887900","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}