Transportation Research Part B-Methodological最新文献

{"title":"Learning to generate synthetic human mobility data: A physics-regularized Gaussian process approach based on multiple kernel learning","authors":"Ekin Uğurel ,&nbsp;Shuai Huang ,&nbsp;Cynthia Chen","doi":"10.1016/j.trb.2024.103064","DOIUrl":"10.1016/j.trb.2024.103064","url":null,"abstract":"<div><div>Passively-generated mobile data has grown increasingly popular in the travel behavior (or human mobility) literature. A relatively untapped potential for passively-generated mobile data is synthetic population generation, which is the basis for any large-scale simulations for purposes ranging from state monitoring, policy evaluation, and digital twins. And yet, this significant potential may be hindered by the growing sparsity or rate of missingness in the data, which stems from heightened privacy concerns among both data vendors and consumers (users of service platforms generating individual mobile data). To both fulfill the great potential and to address sparsity in the data, there is a need to develop a flexible and scalable model that can capture individual heterogeneity and adapt to changes in mobility patterns. We propose a conditional-generative Gaussian process framework that learns kernel structures characterizing individual mobile data and can provably replicate observed patterns. Our approach integrates physical knowledge to regularize the framework such that the generated data obeys constraints imposed by the built and natural environments (such as those on velocity and bearing). To capture travel behavior heterogeneity at the individual level, we propose a data-driven multiple kernel learning approach to determine the optimal composite kernel for every user. Our experiments demonstrate that: (1) the impact of kernel choice on mobility metrics derived from synthetic data is non-negligible; (2) physics-regularization not only reduces model bias but also improves uncertainty estimates associated with the predicted locations; and (3) the proposed method is robust and generalizes well to varying individuals and modes of travel.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103064"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microscopic Discontinuities Disrupting Hydrodynamic and Continuum Traffic Flow Models","authors":"Benjamin Coifman","doi":"10.1016/j.trb.2024.103068","DOIUrl":"10.1016/j.trb.2024.103068","url":null,"abstract":"<div><div>This paper explores short duration disturbances in the traffic stream that are large enough to impact the traffic dynamics and disrupt stationarity when establishing the fundamental diagram, FD, but small enough that they are below the resolution of conventional vehicle detector data and cannot be seen using conventional methods. This empirical research develops the Exclusionary Vehicle Aggregation method (EVA) to extract high fidelity time series data from conventional loop detectors and then extends the method to measure the standard deviation of headways in a given fixed time sample, stdevh. Using loop detector data spanning 18 years and five sites, all of the sites show that samples with low stdevh tend towards a triangular FD while samples with high stdevh tend towards a concave FD that falls inside the triangular FD. The stdevh is also shown to be strongly correlated with the duration of the longest headway within the sample. The presence of a long headway means the state is perceptively different over the sample and thus, the measurement is non-stationary. A review of the earliest FD literature by Greenshields finds strong supporting evidence for these trends. Collectively, the loop detector and historical FD results span over 75 years of empirical traffic data.</div><div>Based on the EVA analysis, this work offers the following insights: the shape of equilibrium FD appears to be triangular and that conventional detector data mask critical features needed by hydrodynamic traffic flow models, HdTFM. Because the driver behind a long headway can act independent of their leader, the long headways can correspond to unobserved boundary conditions that generate kinematic waves. If these boundaries were detected many HdTFM could accommodate them, especially multi-class models. But the stochastic nature of the long headways also challenges the predictive abilities of deterministic HdTFM. Perhaps the largest of these challenges is driver agency- the driver behind a long headway can maintain it, resulting in signals propagating downstream or they can close the gap, resulting in signals propagating upstream. Meanwhile, this work provides a test for stationary conditions to help ensure an empirical FD supports the assumptions placed upon it.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103068"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593876","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":"Stability analysis of a departure time choice problem with atomic vehicle models","authors":"Koki Satsukawa ,&nbsp;Kentaro Wada ,&nbsp;Takamasa Iryo","doi":"10.1016/j.trb.2024.103039","DOIUrl":"10.1016/j.trb.2024.103039","url":null,"abstract":"<div><div>In this study, we analyse the global stability of the equilibrium in a departure time choice problem using a game-theoretic approach that deals with atomic users. We first formulate the departure time choice problem as a strategic game in which atomic users select departure times to minimise their trip cost; we call this game the ‘departure time choice game’. The concept of the epsilon-Nash equilibrium is introduced to ensure the existence of pure-strategy equilibrium corresponding to the departure time choice equilibrium in conventional fluid models. Then, we prove that the departure time choice game is a weakly acyclic game. By analysing the convergent better responses, we clarify the mechanisms of global convergence to equilibrium. This means that the epsilon-Nash equilibrium is achieved by sequential better responses of users, which are departure time changes to improve their own utility, in an appropriate order. Specifically, the following behavioural rules are important to ensure global convergence: (i) the adjustment of the departure time of the first user departing from the origin to the corresponding equilibrium departure time and (ii) the fixation of users to their equilibrium departure times in order (starting with the earliest). Using convergence mechanisms, we construct evolutionary dynamics under which global stability is guaranteed. We also investigate the stable and unstable dynamics studied in the literature based on convergence mechanisms, and gain insight into the factors influencing the different stability results. Finally, numerical experiments are conducted to demonstrate the theoretical results.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103039"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensor placement considering the observability of traffic dynamics: On the algebraic and graphical perspectives","authors":"Xinyue Hu,&nbsp;Yueyue Fan","doi":"10.1016/j.trb.2024.103057","DOIUrl":"10.1016/j.trb.2024.103057","url":null,"abstract":"<div><div>In this paper, we present a new sensor location model that aims to maximize observability of link densities in a dynamic traffic network described using a piecewise linear system of ordinary differential equations. We develop an algebraic approach based on the eigenstructure to determine the sensor location for achieving full observability with a minimal number of sensors. Additionally, a graphical approach based on the concept of structural observability is developed. By exploiting the special property of flow conservation in traffic networks, we derive a simple analytical result that can be used to identify observable components in a partially observable system, which is the main contribution of this paper. The graphical and algebraic properties of observability are then integrated into a sensor location optimization model considering a wide range of traffic conditions. Through numerical experiments, we demonstrate the good performance of our sensor deployment strategies in terms of the average observability and estimation errors.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103057"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining time dependency and behavioral game: A Deep Markov Cognitive Hierarchy Model for human-like discretionary lane changing modeling","authors":"Kehua Chen ,&nbsp;Meixin Zhu ,&nbsp;Lijun Sun ,&nbsp;Hai Yang","doi":"10.1016/j.trb.2024.102980","DOIUrl":"10.1016/j.trb.2024.102980","url":null,"abstract":"<div><div><span>Human drivers take discretionary lane changes when the target lane is perceived to offer better traffic conditions. Improper discretionary lane changes, however, lead to traffic congestion or even crashes. Considering its significant impact on traffic flow efficiency and safety, accurate modeling and prediction of discretionary lane-changing (LC) behavior is an important component in microscopic traffic analysis. Due to the interaction process and driver behavior stochasticity<span>, modeling discretionary lane-changing behavior is a non-trivial task. Existing approaches include rule-based, utility-based, game-based, and data-driven ones, but they fail to balance the trade-off between modeling accuracy and interpretability. To address this gap, we propose a novel model, called Deep Markov Cognitive Hierarchy Model (DMCHM) which combines time dependency and behavioral game interaction for discretionary lane-changing modeling. Specifically, the lane-changing interaction process between the subject vehicle and the following vehicle in the target lane is modeled as a two-player game. We then introduce three dynamic latent variables for interaction aggressiveness, cognitive level, and payoffs based on the Hidden Markov Model<span>. The proposed DMCHM combines time dependency together with cognitive hierarchy behavioral games while preserving model interpretability. Extensive experiments on three real-world driving datasets demonstrate that DMCHM outperforms other game-theoretic baselines and has comparable performance with state-of-the-art deep learning methods in time and location errors. Besides, we employ SHAP values to present the model interpretability. The analysis reveals that the proposed model has good performance in discretionary LC prediction with high interpretability. Finally, we conduct an agent-based simulation to investigate the impact of various driving styles on macroscopic traffic flows. The simulation shows that the existence of massive aggressive drivers can increase traffic capacity because of small gaps during car-following, but inversely decrease discretionary LC rates. A balanced mixing of conservative and aggressive driving styles promotes discretionary LC frequencies since conservative car-following behaviors provide more spaces for LC. The codes can be found at </span></span></span><span><span>https://github.com/zeonchen/DMCHM</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 102980"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594047","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":"Optimal operation strategies of an urban crowdshipping platform in asset-light, asset-medium, or asset-heavy business format","authors":"Zhuoye Zhang,&nbsp;Fangni Zhang","doi":"10.1016/j.trb.2024.102992","DOIUrl":"10.1016/j.trb.2024.102992","url":null,"abstract":"<div><div><span>This paper investigates the operation strategies of an urban crowdshipping platform, which utilizes the latent capacity of the traveling ‘crowd’ in the transportation system to facilitate parcel delivery. We develop an analytical model to characterize the decision-making and operation strategies of a crowdshipping operator in alternative business formats (asset-light/medium/heavy). Asset-light platforms connect customers with potential carriers in the crowd without involving delivery assets, whereas asset-medium and asset-heavy operators integrate crowd carriers with outsourced or owned delivery fleets, respectively. In particular, we firstly formulate the two-sided market equilibrium of crowdshipping system on account of customers’ willingness to use and crowds’ willingness to serve. Based on the market equilibrium, the crowdshipping operator’s optimal strategies in terms of pricing and/or fleet sizing are identified for profit-maximization or social welfare-maximization in alternative business formats. We show that the introduction of crowdshipping can simultaneously improve the benefits of logistics customers, the crowd, and the crowdshipping platform operator, leading to a win-win-win outcome. Furthermore, we establish analytical conditions for one business format being superior to another. We find that if the externality (or marginal social cost) of an unmatched order is smaller in a particular business format, it will result in larger </span>consumer surplus for customers, greater net benefit for crowd carriers, and more profit for crowdshipping operator. Under mild conditions, the crowdshipping operator adopting the asset-light or asset-medium format can earn a positive profit at the social optimum.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 102992"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594050","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":"Dynamic flow control model and algorithm for metro network under FIFO condition","authors":"Ping Zhang ,&nbsp;Jianjun Wu ,&nbsp;Kai Wang ,&nbsp;Yunchao Qu ,&nbsp;Jiancheng Long","doi":"10.1016/j.trb.2024.103089","DOIUrl":"10.1016/j.trb.2024.103089","url":null,"abstract":"<div><div>Implementing passenger flow control strategies is an effective approach to reducing commuter travel delays and ensuring crowd safety in a congested metro network. Due to the intricacy of the interweaving of passenger flows between various lines and stations, the development of a scientific passenger flow control strategy is challenging in the networked mode of operation. The first-in-first-out (FIFO) rule can ensure service fairness and optimal operation by accurate modeling passenger queuing dynamics, but it is rarely considered in existing studies. Inspired by the traditional dynamic traffic assignment models, we propose a novel passenger flow control model with the FIFO rule to find a more reasonable control strategy for a metro network. Unlike road traffic systems, the FIFO rule is formulated as a set of linear constraints to explicitly capture the passenger queuing properties at origin stations. The passenger flow control problem with the FIFO rule is then modeled as a mixed integer linear programming model, which can significantly reduce the model complexity. To reach a high-quality solution, we propose an efficient rolling horizon decomposition approach. In the algorithm, the planning horizon is rolled forward from the current time, and the effects of subsequent periods are considered at each iteration. Besides, a dynamic procedure for loading passengers is developed to evaluate the bounds between the proposed approach and other flow control strategies. The proposed model and algorithm are then applied to solve the problems in test and real metro networks. The numerical results demonstrate the validity of the model’s properties and the algorithm’s performance.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"190 ","pages":"Article 103089"},"PeriodicalIF":5.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553284","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":"Generating online freight delivery demand during COVID-19 using limited data","authors":"Majid Mirzanezhad ,&nbsp;Richard Twumasi-Boakye ,&nbsp;Tayo Fabusuyi ,&nbsp;Andrea Broaddus","doi":"10.1016/j.trb.2024.103100","DOIUrl":"10.1016/j.trb.2024.103100","url":null,"abstract":"<div><div>Urban freight data analysis is crucial for informed decision-making, resource allocation, and optimizing routes, leading to efficient and sustainable freight operations in cities. Driven in part by the COVID-19 pandemic, the pace of online purchases for at-home delivery has accelerated significantly. However, responding to this development has been challenging given the lack of public data. The existing data may be infrequent because of survey participant non-responses. This data paucity renders conventional predictive models unreliable.</div><div>We address this shortcoming by developing algorithms for data imputation and replication for future urban freight demand given limited ground truth online freight delivery data. Our generic framework is capable of taking in repeated cross-sectional surveys and replicating frequent samples from them. In this paper, our case study is focused on Puget Sound Regional Council (PSRC) household travel survey (HTS) data restricted to the Seattle–Tacoma–Bellevue, WA Metropolitan Statistical Area (MSA). We show how to impute the missing online freight deliveries in our travel survey dataset from ground truth values by making a similarity-based matching between the samples of missing and available online delivery volumes. Empirical and theoretical analyses both demonstrate high veracity of imputation where the estimated freight delivery volumes closely resemble the ground truth values. Utilizing the obtained similarity-based matching, we show how to generate data across future and past travel survey datasets with an emphasis on maintaining some consistent trends across the datasets. This work furthers existing methods in demand estimation for goods deliveries by maximizing available scarce data to generate reasonable estimates that could facilitate policy decisions.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"190 ","pages":"Article 103100"},"PeriodicalIF":5.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553306","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":"Revisiting the traffic flow observability problem: A matrix-based model for traffic networks with or without centroid nodes","authors":"Yue Zhuo ,&nbsp;Hu Shao ,&nbsp;William H.K. Lam ,&nbsp;Mei Lam Tam ,&nbsp;Shuhan Cao","doi":"10.1016/j.trb.2024.103099","DOIUrl":"10.1016/j.trb.2024.103099","url":null,"abstract":"<div><div>This study introduces a graph theory-based model that addresses the link flow observability problem in traffic networks by optimizing passive sensor deployment. The model aims to determine the minimal number of sensors and their optimal placement. It constructs a virtual network and uses isomorphic graph theory to map between the original and virtual networks, ensuring consistency in nodes, links, and link directions. Two formulas are proposed to calculate the minimum number of observable links required across different networks, factoring in links, ordinary nodes, centroid nodes, and added links. Key concepts such as chords, cut sets, and loops, along with their matrices, are analyzed. A matrix-based framework is developed to consider flow conservation conditions. Results show that solving the full link flow observability problem using node flow conservation equations yields a fixed number of sensors with non-unique deployment schemes, Additionally, a resource-constrained sensor network optimization (RSNO) model is presented, employing null space projection (NSP) as an objective function to quantify the impact of budget constraints particularly under the condition if all the link flows cannot be observed. Numerical examples demonstrate the RSNO model's applications.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"190 ","pages":"Article 103099"},"PeriodicalIF":5.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530880","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":"The multi-visit drone-assisted routing problem with soft time windows and stochastic truck travel times","authors":"Shanshan Meng ,&nbsp;Dong Li ,&nbsp;Jiyin Liu ,&nbsp;Yanru Chen","doi":"10.1016/j.trb.2024.103101","DOIUrl":"10.1016/j.trb.2024.103101","url":null,"abstract":"<div><div>We consider a combined truck-drone delivery problem with stochastic truck travel times and soft time windows. A fleet of homogeneous trucks and drones are deployed in pairs to provide delivery services to customers. Each drone can be launched from and retrieved to its truck multiple times, and in each flight, a drone can serve one or more customers. Our objective is to determine the truck routes and drone flights that minimise the total cost, including time window violation penalties. We formulate this problem into a two-stage stochastic model with recourse action in the second stage to optimise the truck waiting time at each node. We approximate the stochastic model with a large-scale mixed-integer program using the sample average approximation (SAA) framework, which is computationally intractable. To this end, we propose a hybrid metaheuristic approach that incorporates SAA. The waiting times of each truck obtained in the planning phase are optimal against the sampled or estimated travel times along the entire route, but the actual values are known only once the truck has returned to the depot. To this end, we reformulate the second-stage model in a rolling-horizon manner, which can be easily implemented and efficiently solved in the execution phase. Extensive numerical experiments demonstrate the strong performance of the proposed metaheuristic approach and rolling-horizon model. The results also highlight the clear benefits of the stochastic modelling approach over its deterministic counterpart, with a pronounced reduction in the total cost in various scenarios.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"190 ","pages":"Article 103101"},"PeriodicalIF":5.8,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530881","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}