Transportation Research Part E-Logistics and Transportation Review最新文献_第3页

Enhancing urban rail transit resilience: Strategic bus resource allocation 增强城市轨道交通弹性：战略性公交资源配置

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-22 DOI: 10.1016/j.tre.2025.104327

Yunqiao Xiang , Yun Wang , Xuedong Yan , Haonan Guo , Yu Zhou

{"title":"Enhancing urban rail transit resilience: Strategic bus resource allocation","authors":"Yunqiao Xiang , Yun Wang , Xuedong Yan , Haonan Guo , Yu Zhou","doi":"10.1016/j.tre.2025.104327","DOIUrl":"10.1016/j.tre.2025.104327","url":null,"abstract":"<div><div>Urban rail transit (URT) systems are integral to urban mobility but are susceptible to disruptions that can substantially impact service continuity and passenger convenience. The increasing incidents of URT disruptions necessitate effective strategies to ensure robust and resilient transit operations. Temporarily requisition regular buses to serve as bridging services has become a common strategy to mitigate the adverse effects of URT service disruptions. This study investigates a novel macro-level integration planning problem of regular buses, aiming to optimize both regular bus resource allocation (including depot location, vehicle fleet and vehicle-to-line assignment) and bus bridging services in response to URT disruptions (including the mapping relationships between regular bus depots, requisitioning buses and URT stations), with the goal of minimize operational disruptions and enhance service reliability. A bi-objective integer programming model is developed to integrate regular bus service planning with bus bridging services in response to URT disruptions, minimizing the total deadheading time and reducing the number of unserved passengers. An augmented ε-constraint method, combined with lexicographic optimization and a utopian point, is proposed to generate balanced Pareto optimal solutions. The model is tested through case studies involving both small-scale (part of the Nanchang Metro network) and large-scale (entire Nanchang Metro network, Nanjing Metro network and Chengdu Metro network) disruptions, based on real-world data. Results demonstrate that our approach can produce high-quality solutions that significantly enhance the operational efficiency and responsiveness of bus services to URT disruptions. These strategies ensure smooth operation of regular bus services, mitigate the impacts of URT disruptions, and promote cost-effective utilization of bus resources.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104327"},"PeriodicalIF":8.3,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678862","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}

引用次数: 0

Inventory routing problem of automotive parts considering time-varying demands: A machine learning enhanced branch-and-price approach 考虑时变需求的汽车零部件库存路径问题：一种机器学习增强的分支和价格方法

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104297

Yu Wang , Renrong Zheng , Chengji Liang , Jian Shi

{"title":"Inventory routing problem of automotive parts considering time-varying demands: A machine learning enhanced branch-and-price approach","authors":"Yu Wang , Renrong Zheng , Chengji Liang , Jian Shi","doi":"10.1016/j.tre.2025.104297","DOIUrl":"10.1016/j.tre.2025.104297","url":null,"abstract":"<div><div>With the rise of mass customization and smart manufacturing, the automotive industry is rapidly transitioning to improve responsiveness, manage highly diversified customer orders, and reduce inbound logistics costs. To address this challenge, this paper proposes a new variant of the multi-period inventory routing problem, which focuses on coordinating discrete, time-varying demands for auto parts on the assembly line with predetermined packages at suppliers over a finite short-term time horizon (e.g., on an hourly basis). The objective is to minimize the total transportation and inventory cost by making aperiodic decisions on collection quantities and traveling routes simultaneously for an inbound warehouse near the assembly plant. An integer programming (IP) formulation with time-indexed variables is tailored for the problem to analyze the feasibility conditions. Then, a reformulation is designed to make the problem more tractable, based on which a novel machine learning enhanced branch-and-price algorithm (BPL) is proposed, where prediction-based cuts are embedded to accelerate the pricing procedure. Experiments on real-scale instances demonstrate that the algorithm consistently achieves near-optimal solutions, with a gap of 4.42% on average from the best-found lower bound, and reduces computation time by over 90% compared to directly solving the IP model by CPLEX. The proposed learning technique is computationally efficient, capable of shortening the total calculation time by an average of 13%. This work facilitates timely decision-making and offers new insights into multi-period inventory routing for inbound logistics.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104297"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670407","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}

引用次数: 0

Demand uncertainty aware curbside space allocation planning in shared-use transportation networks 基于需求不确定性的共享交通网络路边空间分配规划

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104245

Shanjeeda Akter, HM Abdul Aziz

{"title":"Demand uncertainty aware curbside space allocation planning in shared-use transportation networks","authors":"Shanjeeda Akter, HM Abdul Aziz","doi":"10.1016/j.tre.2025.104245","DOIUrl":"10.1016/j.tre.2025.104245","url":null,"abstract":"<div><div>Efficient management of curbside space is gaining more attention as cities confront increasing traffic, curbside requirements, and mobility patterns. Given their increasing significance in meeting diverse shared-use mobility requirements, the absence of optimal planning on curbside areas can lead to networkwide negative impacts. This study examines demand uncertainty for planning at several temporal resolutions. Our developed approach identifies the optimal curbside space allocation planning strategies to enhance passenger-level services, considering the <em>Curb Productivity Index</em> and the uncertain arrival distribution of Shared-Use Mobility (SUM) service units throughout the curbside networks. We integrated a core optimization module to adjust capacity over various time scales and find the optimal allocation plan. Further, we integrated a sample-based heuristic to allow decision-making at multiple levels of granularity (allocating space hourly versus adjustments occurring every five minutes due to interconnected infrastructure technologies or analogous factors). The proposed solution methodology is demonstrated for a network of curbsides with known demand distribution parameters (truncated Normal with mean and standard deviation for hourly demand). The results suggest that the allocation plans are highly sensitive to the decision interval (minutes vs. one-hour), and the coarse-resolution decision-making may overestimate the performance of a curbside allocation plan, underscoring the need for fine-resolution allocation plans in cities.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104245"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670430","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}

引用次数: 0

A data-driven approach for spatio-temporal causal analysis in large-scale urban traffic networks 大型城市交通网络时空因果分析的数据驱动方法

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104244

Pingping Dong , Xiaoning Zhang , Xiaoge Zhang

{"title":"A data-driven approach for spatio-temporal causal analysis in large-scale urban traffic networks","authors":"Pingping Dong , Xiaoning Zhang , Xiaoge Zhang","doi":"10.1016/j.tre.2025.104244","DOIUrl":"10.1016/j.tre.2025.104244","url":null,"abstract":"<div><div>Understanding causal relationships between traffic states throughout the system is of great significance for enhancing traffic management and optimization in urban traffic networks. Unfortunately, few studies in the literature have systematically analyzed causal structure characterizing the evolution of traffic states over time and gauged the importance of traffic nodes from a causal perspective, particularly in the context of large-scale traffic networks. Moreover, the dynamic nature of traffic patterns necessitates a robust method to reliably discover causal relationships, which are often overlooked in existing studies. To address these issues, we propose a Spatio-Temporal Causal Structure Learning and Analysis (STCSLA) framework for analyzing large-scale urban traffic networks at a mesoscopic level from a causal lens. The proposed framework comprises three main components: decomposition of spatio-temporal traffic data into localized traffic subprocesses; a Bayesian Information Criterion-guided spatio-temporal causal structure learning combined with temporal-dependencies preserving sampling for deriving reliable causal graph to uncover time-lagged and contemporaneous causal effects; establishing several causality-oriented indicators to identify causally critical nodes, mediator nodes, and bottleneck nodes in traffic networks. Experimental results on both a synthetic dataset and the real-world Hong Kong traffic dataset demonstrate that the proposed STCSLA framework accurately uncovers time-varying causal relationships and identifies key nodes that play various causal roles in influencing traffic dynamics. These findings underscore the potential of the proposed framework to improve traffic management and provide a comprehensive causality-driven approach for analyzing urban traffic networks.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104244"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670428","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}

引用次数: 0

Competitive strategies in digital service capability: Self-Development vs. Cooperation 数字服务能力的竞争策略：自我发展vs.合作

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104291

Tao Zhou , Kai Li , Bohai Liu , Fulong Xie , Liping Xu , Han Zhang

{"title":"Competitive strategies in digital service capability: Self-Development vs. Cooperation","authors":"Tao Zhou , Kai Li , Bohai Liu , Fulong Xie , Liping Xu , Han Zhang","doi":"10.1016/j.tre.2025.104291","DOIUrl":"10.1016/j.tre.2025.104291","url":null,"abstract":"<div><div>We examine various competition modes arising from the deployment of the digital service capabilities by two competing digital companies in smart product service systems, and analyze the effects of digital service value-addition, the alignment between smart products and digital services on the operations of rival parties. We construct game-theoretic competition models to derive the optimal deployment strategy for digital companies’ digital service capabilities, as well as to determine the optimal digital service level and pricing strategy. According to the sub-game perfect equilibrium outcomes derived from a specific competition mode, our findings uncover that even if a party’s digital service capability is weaker, its digital company still possesses the potential to outperform its rival in terms of profitability. Additionally, an increase in value-addition offered by digital services can undermine digital companies’ profitability. Likewise, the heightened alignment between smart products and digital services can be detrimental to digital companies. Furthermore, our analysis unveils that when the digital service capabilities of both competitors are strong, one of the digital companies will deviate from the symmetrical digital service capability deployment strategy, resulting in an asymmetrical equilibrium in which one company invests internally to develop a digital service capability, while the other partners with an external provider. On the contrary, when the digital service capabilities are weak, both competing digital companies opt to invest internally to deploy the digital service capability. However, this symmetrical equilibrium strategy ultimately places both digital companies in a prisoner’s dilemma.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104291"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670429","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}

引用次数: 0

Platform-empowered collaboration delivery model for express companies and rural passenger transport operators in rural areas 面向农村地区快递公司和农村客运经营者的平台化协同配送模式

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104311

Weizhen Rao, Xiaohe Miao, Peng Liu, Lu Liu

{"title":"Platform-empowered collaboration delivery model for express companies and rural passenger transport operators in rural areas","authors":"Weizhen Rao, Xiaohe Miao, Peng Liu, Lu Liu","doi":"10.1016/j.tre.2025.104311","DOIUrl":"10.1016/j.tre.2025.104311","url":null,"abstract":"<div><div>The rapid surge in e-commerce parcel volume has intensified demands for cost-effective and high-quality express delivery services in rural areas. This study proposes a platform-enabled collaborative delivery model that integrates express companies and rural passenger transport operators to improve last-mile logistics. Our goal is to facilitate efficient collaboration among stakeholders through platform-supported route planning and cost-sharing, with cost savings quickly estimated for decision-making. To assess the benefits of shared transport resources, we adopt a Shapley value-based cooperative game approach to determine cost allocation. This requires solving mixed-integer programming models for all possible alliance structures to compute characteristic functions. A mixed-integer linear programming model is formulated to address the multi-owner collaborative delivery vehicle routing problem with combined passenger and freight transport (MOCDVRP-CPFT), which quantifies delivery costs for each alliance configuration. A tailored solution framework is developed, incorporating batch processing, customer clustering, and an adaptive large neighbourhood search (ALNS) algorithm to generate high-quality solutions across all alliances. Six representative case studies in eastern, central, and western China using real-world data confirm the effectiveness of the proposed model, with the most significant savings observed in the western region. Based on the results, we offer region-specific policy suggestions to facilitate the implementation of CPFT in varying rural contexts. This study highlights the potential of digitally enabled, short-term collaborative alliances as a practical approach to improving rural logistics coordination and delivery efficiency.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104311"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670427","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}

引用次数: 0

Simultaneous estimation of induced, diverted, and ex-post demand for railway passengers: an interpretable machine learning framework based on constrained computational graphs 铁路乘客诱导、分流和事后需求的同时估计：基于约束计算图的可解释机器学习框架

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104283

Xin Wu , Xinyu Wang , Taehooie Kim , Khaled Saleh , Huiling Fu , Chenfeng Xiong

{"title":"Simultaneous estimation of induced, diverted, and ex-post demand for railway passengers: an interpretable machine learning framework based on constrained computational graphs","authors":"Xin Wu , Xinyu Wang , Taehooie Kim , Khaled Saleh , Huiling Fu , Chenfeng Xiong","doi":"10.1016/j.tre.2025.104283","DOIUrl":"10.1016/j.tre.2025.104283","url":null,"abstract":"<div><div>Passenger flow on train lines is driven by how travelers respond to service offerings and constraints within the railway system, shaped primarily by three factors: <strong>Diverted demand</strong> refers to a shift in travelers’ choices toward different train lines, quantified by analyzing changes in the probability of selecting a particular train line within a given line plan. <strong>Induced demand</strong> arises when improvements in service quality led to an increase in passenger demand within a railway system. <strong>Ex-post demand</strong> occurs when seat capacity constraints force travelers to make choices that deviate from their initial preferences. This paper aims to develop a systematic and theoretically consistent methodology to estimate the three types of demand that drive overall demand variation. To integrate these estimation modules, a computational graph-based learning architecture is proposed to solve the railway passenger demand estimation (RPDE) problem. The RPDE problem simultaneously estimates passenger boarding and alighting at stations, OD trips between stations, and passenger flows loaded onto train lines. The behavioral parameters associated with travel time, ticket price, and line frequency are also calibrated. A novel four-stage adapted alternating direction method of multipliers (ADMM), enhanced by backpropagation, is proposed to solve the RPDE problem to ensure consistency between modules and enable efficient solutions. We demonstrate the effectiveness of the method through scenario analyses, quantifying the composition of the demand, and revealing their implications for policymaking. A real-world case study in the Beijing-Shanghai high-speed rail corridor is used to demonstrate the applicability of the proposed approach.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104283"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670409","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}

引用次数: 0

Enhanced supply chain resilience under geopolitical risks: The role of artificial intelligence 地缘政治风险下供应链弹性增强：人工智能的作用

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-21 DOI: 10.1016/j.tre.2025.104300

Feng Dong , Xu Zhao , Sachin Kumar Mangla , Malin Song

{"title":"Enhanced supply chain resilience under geopolitical risks: The role of artificial intelligence","authors":"Feng Dong , Xu Zhao , Sachin Kumar Mangla , Malin Song","doi":"10.1016/j.tre.2025.104300","DOIUrl":"10.1016/j.tre.2025.104300","url":null,"abstract":"<div><div>This paper examines the impact of artificial intelligence (AI) on supply chain resilience (SCR) under geopolitical risks (GPR) through a tractable research framework and empirical analysis. We first develop a general equilibrium model with stochastic supply chain shocks to specify the underlying economic mechanism. The results show that the existence of geopolitical factors will increase the risk cost of firms maintaining supply chain relations, thus weakening SCR. However, the significant cost reductions, efficiency gains, and improvement of contractual completeness resulting from AI greatly empower firms to increase profits, thereby mitigating the disruption of uncertain risks to the supply chain, which leads to enhanced SCR. AI could mitigate the negative effects of GPR to a certain extent, but this depends on the relative magnitude of the positive and negative incentive effects of AI. We then perform two-way fixed effects estimations using data on Chinese listed firms. The empirical results validate our main theoretical analysis and confirm the role of firm profit as a bridge between AI and SCR, along with its attendant premise. Our further exploration confirms the moderating effect of AI in high-tech and high-competition industries, which may be attributed to the predominance of positive incentive effects of AI. Finally, our analysis results call for firms to strike a balance between the breadth and depth of AI applications, thus comprehensively strengthening the ability of the supply chain to cope with uncertainty.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104300"},"PeriodicalIF":8.3,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144678859","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}

引用次数: 0

Expansion of bi-modal express transit networks − a hybrid optimization approach 双式联运快速交通网络的扩展——一种混合优化方法

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-19 DOI: 10.1016/j.tre.2025.104317

Reza Mahmoudi, Saeid Saidi, S.C. Wirasinghe

{"title":"Expansion of bi-modal express transit networks − a hybrid optimization approach","authors":"Reza Mahmoudi, Saeid Saidi, S.C. Wirasinghe","doi":"10.1016/j.tre.2025.104317","DOIUrl":"10.1016/j.tre.2025.104317","url":null,"abstract":"<div><div>Existing research has predominantly concentrated on designing a new transit network without considering the pre-existing network. However, the majority of problems involve redesigning or extending an already existing network. Considering the pre-existing multi-modal transit network in a city, we have integrated analytical methodologies and mathematical programming to formulate a two-stage approach for addressing the bi-modal express transit network design problem (ETNDP) within the context of a surface express transit system. In the first stage, we use analytical approaches and continuum approximations to identify the optimal locations of new stations. In the second stage, mathematical programming is proposed to simultaneously determine the optimal layout of express transit routes, the technology of each transit route, and the service headway associated with all transit routes (i.e., existing and new routes). Then, a metaheuristic algorithm based on a Genetic Algorithm is introduced to solve the proposed mathematical programming for real-size transit networks. The proposed approach has then been applied to the express transit network of Calgary, Canada, a large-sized bi-modal express network. The bi-modal ETNDP has been solved for Calgary under various scenarios, and the results have been discussed. Analyses show that, in the proposed hybrid approach, solving a part of the problem analytically reduces its complexity significantly and enables parametric analysis, while using mathematical programming helps to address the complexity of ETNDP for real transit networks. The proposed approach stands out from existing similar studies due to its departure from simplifying assumptions concerning network topology, the city’s structure, capturing any type of demand patterns, model flexibility to for existing transit network extension, and multi-modality of the express transit network.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104317"},"PeriodicalIF":8.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663416","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}

引用次数: 0

Optimizing land-air collaborative operations with environmental considerations 考虑环境因素，优化陆空协同作战

IF 8.3 1区工程技术

Transportation Research Part E-Logistics and Transportation Review Pub Date : 2025-07-19 DOI: 10.1016/j.tre.2025.104301

Honggang Zhang , Yuyan Wang , Mengyu Jiang , Zefan Huang , King-Wah Pang , Zhiyuan Liu

{"title":"Optimizing land-air collaborative operations with environmental considerations","authors":"Honggang Zhang , Yuyan Wang , Mengyu Jiang , Zefan Huang , King-Wah Pang , Zhiyuan Liu","doi":"10.1016/j.tre.2025.104301","DOIUrl":"10.1016/j.tre.2025.104301","url":null,"abstract":"<div><div>Urban air mobility (UAM) is an emerging transportation concept with the potential to transform urban commuting. By utilizing low-altitude airspace, novel aerial vehicles can provide faster transportation between vertiports in urban and suburban areas, offering a more efficient alternative than traditional surface transport. To successfully integrate UAM into urban environments, it is crucial to effectively connect it with existing road transportation systems, particularly in terms of constructing essential ground infrastructure, such as vertiports. This paper proposes a land-air collaborative network design model that incorporates environmental considerations. Specifically, we develop a bi-objective bi-level programming model to optimize the land-air integrated operations. The upper-level authority aims to minimize both the total travel time of the system and airborne pollutant emissions during UAM operations by selecting the locations and capacities of vertiports. The lower-level model determines the route choices of the multi-class commuters based on the user equilibrium condition. To solve this model, we propose a mixed-integer Bayesian optimization approach, incorporating a path-based solution algorithm using the partial linearization descent method to address the lower-level model. Numerical experiments demonstrate that incorporating environmental considerations significantly influences the design of the land-air collaborative network. In particular, environmental factors play a critical role in shaping commuters’ route choice, which in turn substantially affects key system metrics such as vertiport capacity, total travel time, and air pollutant emissions. This study offers valuable insights into optimizing land-air collaborative operations, maximizing the operational benefits of UAM while minimizing its environmental impact.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104301"},"PeriodicalIF":8.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663418","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}

引用次数: 0