Transportation Research Part B-Methodological最新文献

{"title":"A topological network connectivity design problem based on spectral analysis","authors":"Shoichiro Nakayama ,&nbsp;Shun-ichi Kobayashi ,&nbsp;Hiromichi Yamaguchi","doi":"10.1016/j.trb.2024.103012","DOIUrl":"10.1016/j.trb.2024.103012","url":null,"abstract":"<div><div>How to improve network connectivity and which parts of the network are vulnerable are critical issues. We begin by defining an equal distribution problem, in which supplies are distributed equally to all nodes in the network. We then derive a topological network connectivity measure from the convergence speed, which is the second minimum eigenvalue of a Laplacian network matrix. Based on the equal distribution problem, we propose a method for identifying critical links for network connectivity using the derivative of the second minimum eigenvalue. Furthermore, we develop a network design problem that maximizes topological connectivity within a budget creating strengthening network links. The problem is convex programming, and the solution is global. Furthermore, it can be converted into an identical semidefinite programming problem, which requires less computational effort. Finally, we test the developed problems on road networks in the Japanese prefectures of Ishikawa and Toyama to determine their applicability and validity.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103012"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594070","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 OD-based up-front discounting strategies for enroute ridepooling services","authors":"Siying Wang ,&nbsp;Xiaolei Wang ,&nbsp;Chen Yang ,&nbsp;Xiaoning Zhang ,&nbsp;Wei Liu","doi":"10.1016/j.trb.2024.103013","DOIUrl":"10.1016/j.trb.2024.103013","url":null,"abstract":"<div><div>The technological progress in the recent decade has greatly facilitated the large-scale implementation of dynamic enroute ridepooling services, such as Uber Pool and DiDi Pinche. To sustain a profitable enroute ridepooling service, a well-designed discounting scheme is crucial. This paper focuses on the optimization of up-front discounting strategies for enroute ridepooling service, under which passengers are notified of origin–destination(OD)-based discount ratios together with estimated ride time before the start of their trips and enjoy the discounted prices no matter if they succeed or fail to get matched afterward. Assuming that ridepooling demand of each OD pair decreases with its price and the estimated waiting and ride time, we propose to optimize the discounting strategy of each OD pair through two methods. In the first method, the ridepooling price of each OD pair is optimized independently and adjusted day-to-day based on historical information; and in the second method, we optimize the prices of all OD pairs simultaneously, with the complex interactions among the expected ride and waiting times and the demand rates of all OD pairs being considered and captured by a system of nonlinear equations. The nonlinear and non-convex optimization problem of the second method is solved by two derivative-free algorithms: Bayesian optimization<span> and classification-based optimization. Based on a 15*15 grid network with 30 OD pairs and the real road network of Haikou (China), we conduct simulation experiments to examine the efficiency of the two algorithms and the system performance under different discounting strategies derived from the two methods. It is found that in comparison with a uniform discounting strategy, OD-based discounting strategies generated by both methods can bring about 3.84% more profit to the platform. In comparison with the independently optimized discounting strategies generated by the first method, the system optimal discounting strategy generated by the second method can further improve the platform profit by 5.55% and 2.71% on average in our grid-network and real road network experiments.</span></div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103013"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594071","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":"Providing real-time en-route suggestions to CAVs for congestion mitigation: A two-way deep reinforcement learning approach","authors":"Xiaoyu Ma,&nbsp;Xiaozheng He","doi":"10.1016/j.trb.2024.103014","DOIUrl":"10.1016/j.trb.2024.103014","url":null,"abstract":"<div><div>This research investigates the effectiveness of information provision for congestion reduction in Connected Autonomous Vehicle (CAV) systems. The inherent advantages of CAVs, such as vehicle-to-everything communication, advanced vehicle autonomy<span>, and reduced human involvement, make them conducive to achieving Correlated Equilibrium<span> (CE). Leveraging these advantages, this research proposes a reinforcement learning framework involving CAVs and an information provider, where CAVs conduct real-time learning to minimize their individual travel time, while the information provider offers real-time route suggestions aiming to minimize the system’s total travel time. The en-route routing problem<span> of the CAVs is formulated as a Markov game and the information provision problem is formulated as a single-agent Markov decision process<span>. Then, this research develops a customized two-way deep reinforcement learning approach to solve the interrelated problems, accounting for their unique characteristics. Moreover, CE has been formulated within the proposed framework. Theoretical analysis rigorously proves the realization of CE and that the proposed framework can effectively mitigate congestion without compromising individual user optimality. Numerical results demonstrate the effectiveness of this approach. Our research contributes to the advancement of congestion reduction strategies in CAV systems with the mitigation of the conflict between system-level and individual-level goals using CE as a theoretical foundation. The results highlight the potential of information provision in fostering coordination and correlation among CAVs, thereby enhancing traffic efficiency and achieving system-level goals in smart transportation.</span></span></span></span></div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103014"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594072","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":"Bridging the gap between micro-economics and micro-mobility: A two-dimensional risk-based microscopic model of pedestrians’ and bicyclists’ operational behaviors","authors":"Mohaiminul Haque ,&nbsp;Samer H. Hamdar ,&nbsp;Alireza Talebpour","doi":"10.1016/j.trb.2024.103021","DOIUrl":"10.1016/j.trb.2024.103021","url":null,"abstract":"<div><div>Due to the inherent safety concerns associated with traffic movement in unconstrained two-dimensional settings, it is important that pedestrians’ and other modes’ movements such as bicyclists are modeled as a risk-taking stochastic dynamic process that may lead to errors and thus contacts and collisions. Among the existing models that may capture risk-taking behaviors are: 1) the social force models (through the interplay of the repulsion and the attraction force parameters); 2) and the discrete-choice models (through the rationality or the bounded rationality paradigm while weighing different alternatives). Given that the social force models may not readily capture the contact/collision dynamics through the Newtonian force framework, decision-making theories are hypothesized as a feasible approach to formulate a new model that can account for cognitive and behavioral dimensions such as uncertainty and risk. However, instead of relying on the bounded rationality theory, in this paper, a generalized Prospect Theory based microsimulation model is proposed. The model relies on the micro-economics Prospect Theory paradigm where pedestrians or bicyclists (i.e., micro-mobility users) evaluate their speed and directional alternatives while considering the possibility of colliding with other obstacles/users. A numerical analysis on the main model parameters is presented. The model is then calibrated and validated using two real-world data sets with trajectories recorded in naturalistic settings. With the calibrated parameters studied, simulation exercises and sensitivity analysis are conducted to recreate bottlenecks and lane formations in different conditions. The findings show that the proposed model's parameters reflect the risk-taking tendencies of different roadway users in mixed right-of-way's environments while showing realistic microscopic and macroscopic traffic flow characteristics.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103021"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594074","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 generalized rationally inattentive route choice model with non-uniform marginal information costs","authors":"Bo Zhou ,&nbsp;Ronghui Liu","doi":"10.1016/j.trb.2024.102993","DOIUrl":"10.1016/j.trb.2024.102993","url":null,"abstract":"<div><div>Information consumes attention. In the information-rich society, a wealth of information can support decision-making, but it can also create poverty of attention to and inability to make the best use of information. This study applies the theory of rational inattention in modelling traveller’s route choice behaviour, where the attention (costs) to information is non-uniform. We establish the mathematical formulation of a generalized rationally inattentive route choice model with non-uniform marginal information costs, and prove that the optimal conditional route choice probabilities for all the routes always locate within the interior of the feasible region of the route choice model. Based on this property, we analytically characterize the closed-form expression of the optimal conditional choice probabilities, and devise an efficient iterative solution algorithm to compute them. Finally, two numerical examples are conducted to demonstrate the theoretical properties of the rationally inattentive route choice behaviour. This behavioural modelling approach provides an insight on how the rationally inattentive travellers spontaneously learn the optimal route choice from the acquired information.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 102993"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594051","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":"Integrated departure and boundary control for low-altitude air city transport systems","authors":"Yazan Safadi ,&nbsp;Nikolas Geroliminis ,&nbsp;Jack Haddad","doi":"10.1016/j.trb.2024.103020","DOIUrl":"10.1016/j.trb.2024.103020","url":null,"abstract":"<div><div>Connectivity and digitalization will enable new control measures in urban air mobility operations and open new ways for integrating these measures in real-time traffic management. Hence, new control strategies can be designed to regulate both demand and supply of Low-Altitude Air city Transport (LAAT) systems. This can be achieved by adjusting aircraft departure times, and manipulating transfer aircraft flows at boundary air regions. In this research, new model-based control strategies are designed, where aircraft departure management and boundary control strategies are integrated. The aviation operation can benefit from the proposed flow-oriented control paradigm, which can balance the LAAT system’s <em>supply</em> and <em>demand</em>, i.e. controlling the transfer flow between airspace regions and simultaneously managing the aircraft departure (inflow). The current paper presents the development of different control strategies: Departure Controller (DC), Boundary Controller (BC), and integrated Departure and Boundary Controller (DBC), with supporting simulation results. The designed controllers are tested in a new LAAT framework that considers modeling and control of LAAT operation while capturing the microscopic and macroscopic levels simultaneously.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103020"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594073","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":"Markov game for CV joint adaptive routing in stochastic traffic networks: A scalable learning approach","authors":"Shan Yang ,&nbsp;Yang Liu","doi":"10.1016/j.trb.2024.102997","DOIUrl":"10.1016/j.trb.2024.102997","url":null,"abstract":"<div><div>This study proposes a learning-based approach to tackle the challenge of joint adaptive routing in stochastic traffic networks with Connected Vehicles (CVs). We introduce a Markov Routing Game (MRG) to model the adaptive routing behavior of all vehicles in such networks, thereby incorporating both competitive route choices and real-time decision-making. We establish the existence of the Nash policy (i.e., optimal joint adaptive routing policy) within the MRG that enables vehicles to adapt optimally to real-time traffic conditions online through efficient communication. To enhance scalability, we innovate with a homogeneity-based mean-field approximation method and, based on that, further develop the Homogeneity-based Mean-Field Deep Reinforcement Learning (HMF-DRL) algorithm to learn the Nash policy within the MRG. Through numerical experiments on the Nguyen–Dupuis network, we demonstrate our algorithm’s ability to efficiently converge and learn the joint adaptive routing policy that significantly enhances traffic network efficiency. Furthermore, our study provides insights into the effects of travel demand, penetration of CVs, and levels of uncertainty on the performance of the joint adaptive routing policy. This paper presents a significant step towards improving network efficiency and reducing the travel time for a majority of vehicles amid uncertain traffic conditions.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 102997"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594053","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":"Preface to ISTTT Special Issue Volume 189, Transportation Research Part B","authors":"H. Michael Zhang ,&nbsp;Yafeng Yin ,&nbsp;Henry X. Liu","doi":"10.1016/j.trb.2024.103103","DOIUrl":"10.1016/j.trb.2024.103103","url":null,"abstract":"","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103103"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594111","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":"Design an intermediary mobility-as-a-service (MaaS) platform using many-to-many stable matching framework","authors":"Rui Yao,&nbsp;Kenan Zhang","doi":"10.1016/j.trb.2024.102991","DOIUrl":"10.1016/j.trb.2024.102991","url":null,"abstract":"<div><div>Mobility-as-a-service (MaaS) provides seamless door-to-door trips by integrating different transport modes. Although many MaaS platforms have emerged in recent years, most of them remain at a limited integration level. This study investigates the assignment and pricing problem for a MaaS platform as an intermediary in a multi-modal transportation network, which purchases capacity from service operators and sells multi-modal trips to travelers. The analysis framework of many-to-many stable matching is adopted to decompose the joint design problem and to derive the stability condition such that both operators and travelers are willing to participate in the MaaS system. To maximize the flexibility in route choice and remove boundaries between modes, we design an origin–destination pricing scheme for MaaS trips. On the supply side, we propose a wholesale purchase price for service capacity. Accordingly, the assignment problem is reformulated and solved as a bi-level program, where MaaS travelers make multi-modal trips to minimize their travel costs meanwhile interacting with non-MaaS travelers in the multi-modal transport system. We prove that, under the proposed pricing scheme, there always exists a stable outcome to the overall many-to-many matching problem. Further, given an optimal assignment and under some mild conditions, a unique optimal pricing scheme is ensured. Numerical experiments conducted on the extended Sioux Falls network also demonstrate that the proposed MaaS system could create a win-win-win situation—the MaaS platform is profitable and both traveler welfare and transit operator revenues increase from a baseline scenario without MaaS.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 102991"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594049","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":"Estimation of schedule preference and crowding perception in urban rail corridor commuting: An inverse optimization method","authors":"Pu Xu ,&nbsp;Tian-Liang Liu ,&nbsp;Qiong Tian ,&nbsp;Bingfeng Si ,&nbsp;Wei Liu ,&nbsp;Hai-Jun Huang","doi":"10.1016/j.trb.2024.103023","DOIUrl":"10.1016/j.trb.2024.103023","url":null,"abstract":"<div><div>This paper introduces an inverse optimization method to uncover commuters’ schedule preference and crowding perception based on aggregated observations from smart card data for an urban rail corridor system. The assessment of time-of-use preferences typically involves the use of econometric models of discrete choice based on detailed travel survey data. However, discrete choice models often struggle with potential endogeneity issues in behavioral observations when estimating individual samples from massive transit data with limited exogenous identifying information. This motivates us to employ an equilibrium modeling approach to capture the dynamism hidden in commuters’ departure time decision-making from aggregations. Assuming user optimality in observed choices, an inverse optimization method is proposed to find a set of preference parameters in the stochastic user equilibrium-based morning commuting model with heterogeneous commuters so that the resulting equilibrium pattern best approximates the observed departure rate distribution over time. The proposed inverse optimization problem can be formulated by a bi-level programming model and a sensitivity analysis-based solution framework is further designed for model estimation. Lastly, the smart card data and train timetable data from the rail corridor along the Beijing Subway Batong Line are synthesized for a case study to estimate commuters’ departure time choice preferences during morning peak periods, as well as to validate the robustness and practicality of the proposed method.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"189 ","pages":"Article 103023"},"PeriodicalIF":5.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594005","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}