Transportation Research Part C-Emerging Technologies最新文献

{"title":"Network-wide critical routes identification and coordinated control based on automatic vehicle identification data","authors":"Peng Chen ,&nbsp;Jiaming Xu ,&nbsp;Yu Mei ,&nbsp;Lei Wei","doi":"10.1016/j.trc.2025.105019","DOIUrl":"10.1016/j.trc.2025.105019","url":null,"abstract":"<div><div>Coordinated signal control is an effective way to improve traffic efficiency in urban road networks. This study presents a network-wide coordinated signal control method based on the identification of critical routes and the partitioning of coordinated intersection groups using automatic vehicle identification (AVI) data. A movement-level network representation model is first proposed to identify critical routes by analyzing the fully sampled paths of individual vehicles extracted from the network’s AVI data. Then, the optimization of the entire road network is divided into multiple coordinated intersection groups and potential isolated intersections by minimizing total delay, accounting for the interactions between cycle length and delay at intersections along all critical routes. Based on the ring-and-barrier scheme, the signal control problem for each coordinated intersection group is formulated as a mixed integer linear programming (MILP) model aimed at maximizing the bandwidth allocated to critical route bands. Utilizing real AVI data collected from the network of Baoding City, China, the experimental results demonstrate that the proposed partitioning method outperforms static clustering methods that rely on traffic state, e.g., density, for control purposes, particularly in coordinated intersection groups. In comparison to state-of-the-art studies, the analyses indicate that the comprehensive framework, which ranges from critical routes identification and network partition to traffic signal control based on AVI data, significantly enhances network performance by reducing the queue length and average delay at intersections.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"172 ","pages":"Article 105019"},"PeriodicalIF":7.6,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349332","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":"Novel pavement crack detection sensor using coordinated mobile robots","authors":"Mohammad Alkhedher ,&nbsp;Abdullah Alsit ,&nbsp;Marah Alhalabi ,&nbsp;Sharaf AlKheder ,&nbsp;Abdalla Gad ,&nbsp;Mohammed Ghazal","doi":"10.1016/j.trc.2025.105021","DOIUrl":"10.1016/j.trc.2025.105021","url":null,"abstract":"<div><div>This paper proposes a novel pavement crack detection sensor using coordinated mobile robots. The comfort of drivers and the economic efficiency are negatively affected by pavement deterioration due to weather and constant vehicle use. Our proposed system consists of a drone and an unmanned ground robot that checks the quality of roads and shows where cracks and other problems are by measuring and reporting all kinds of irregularities in road surfaces in an autonomous manner. The design of our system is a one-of-a-kind dual-cart unmanned ground vehicle, with its first cart being a drone-mounting body. The drone is equipped with a high-resolution camera for the inspection of roads, cracks, and anomalies remotely using image processing and artificial intelligence. In the event that a crack is identified, a signal is sent to the robot, instructing it to carry out a more comprehensive crack inspection. This inspection involves the use of close-range laser depth and thermal cameras to generate the pavement cracks’ depth maps accurately. We incorporate a drone into our proposed coordinated mobile robots system to enable cheaper operations and provide aerial coverage, preventing traffic congestion. Our novel pavement crack detection sensor can be incorporated with governmental agencies such as the Ministry of Transportation, the Municipality, and Civil Defence entities. Pavement and road health surveys can be completed in over fifty percent less time using our coordinated mobile robots system.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"172 ","pages":"Article 105021"},"PeriodicalIF":7.6,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349685","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":"Robust lane change decision for autonomous vehicles in mixed traffic: A safety-aware multi-agent adversarial reinforcement learning approach","authors":"Tao Wang ,&nbsp;Minghui Ma ,&nbsp;Shidong Liang ,&nbsp;Jufen Yang ,&nbsp;Yansong Wang","doi":"10.1016/j.trc.2025.105005","DOIUrl":"10.1016/j.trc.2025.105005","url":null,"abstract":"<div><div>As autonomous driving technology advances, scenarios where autonomous vehicles coexist with human-driven vehicles will become increasingly common. However, existing lane-changing decision models often overlook the vulnerability to adversarial attacks and the complexity of traffic scenarios, leading to the risk of erroneous decisions in mixed traffic flows, which could result in catastrophic consequences. To address these issues, this paper proposes a novel dual-layer lane-changing decision-making algorithm to enhance the safety and reliability of autonomous vehicles in complex environments. The upper layer of the algorithm is based on a Multi-Agent framework, where adversarial learning is used to optimize decision strategies, allowing vehicles to adapt to various interferences and obstacles. The lower layer introduces a collision avoidance mechanism based on the principles of yielding and action masking, effectively reducing the risk of collisions. Experimental results under various traffic densities and disturbance conditions demonstrate that the proposed algorithm significantly improves the robustness of system, safety, and driving efficiency in complex conditions.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"172 ","pages":"Article 105005"},"PeriodicalIF":7.6,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140248","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 prediction models by considering different time granularity of features and target: Problem and solution","authors":"Ran Yan ,&nbsp;Shuo Jiang ,&nbsp;Kai Wang ,&nbsp;Shuaian Wang","doi":"10.1016/j.trc.2025.105002","DOIUrl":"10.1016/j.trc.2025.105002","url":null,"abstract":"<div><div>In many prediction tasks, a common characteristic of training datasets is that features are more frequently updated than target, or in other words, the time granularity, or granularity for short, of features is smaller than that of target. One typical example is predicting ship fuel consumption in maritime transport. <em>Current practice</em> usually ignores such characteristic when developing the prediction models, which may jeopardize prediction accuracy and reliability. However, this issue is neither systematically discussed nor addressed in existing literature. To bridge this gap, this study aims to formally discuss the differences in the granularity of features and target as an ubiquitous issue in prediction problems. Then, an innovative <em>two-stage tree-based approach</em> that considers such differences by maximizing the usage of more frequently updated features is developed. We then go a step further to extend the proposed <em>two-stage tree-based approach</em> to predict accumulative target considering monotonicity and data generation process. Extended numerical experiments using simulated and real datasets in maritime and urban transportation are conducted to verify the superiority of the <em>two-stage tree-based approach</em> and its extension.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"172 ","pages":"Article 105002"},"PeriodicalIF":7.6,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143140247","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":"MoMaS: Two-sided Mobility Market Simulation Framework for Modeling Platform Growth Trajectories","authors":"Farnoud Ghasemi,&nbsp;Rafal Kucharski","doi":"10.1016/j.trc.2024.104990","DOIUrl":"10.1016/j.trc.2024.104990","url":null,"abstract":"<div><div>Mobility platforms such as Uber and DiDi have been introduced in cities worldwide, each demonstrating varying degrees of success, employing diverse strategies, and exerting distinct impacts on urban mobility. We have observed various growth trajectories in two-sided mobility markets and understood the underlying mechanisms. However, to date, a realistic microscopic model of these markets including phenomena such as network effects has been missing. State-of-the-art methods well estimate the macroscopic equilibrium conditions in the market, but struggle to reproduce the individual human behavior behind and complex growth patterns sensitive to platform strategy and policies.</div><div>To bridge this gap, we introduce the <strong>MoMaS</strong> (two-sided Mobility Market Simulation) framework to represent growth mechanism in two-sided mobility markets based on the realistic behavior adjustment of drivers and travelers reactive to platform strategy. In the proposed framework, traveler and driver agents learn the platform utility from multiple channels: their own experience, peers’ word-of-mouth, and the platform’s marketing, all-together constituting the agent’s perceived utility of the platform. Each of these channels is modeled and updated by our S-shaped learning model day-to-day which stabilizes, and at the same time, remains sensitive to the system changes. The platform can simulate any strategy on five levers: trip fare, commission rate, discount rate, incentive rate, and marketing.</div><div>While detailed empirical data and actual strategies for platform growth remain largely unknown, MoMaS allows to reproduce series of plausible growth trajectories that were previously unattainable. The framework facilitates the modeling of individual-level behaviors such as reluctance, neutrality, and loyalty, alongside aggregate-level dynamics like critical mass, bandwagon effects, and both positive and negative cross-side network effects.</div><div>We illustrate the capabilities of MoMaS through an extensive set of real-world experiments. Our results demonstrate that once the platform acquires critical mass, it triggers a significant positive cross-side network effect, accelerating growth. However, this can be reversed if a negative cross-side network effect is triggered, leading to the collapse of the platform. MoMaS is applicable for real-sized problems and available on public repository along with reproducible experiments.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104990"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143104804","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":"A composite transportation network design problem with land-air coordinated operations","authors":"Honggang Zhang ,&nbsp;Jinbiao Huo ,&nbsp;Churong Chen ,&nbsp;Zhiyuan Liu","doi":"10.1016/j.trc.2024.104967","DOIUrl":"10.1016/j.trc.2024.104967","url":null,"abstract":"<div><div>With the advent of electric vertical-takeoff-and-landing (eVTOL) vehicles, it becomes imperative to assess their impact on transportation network efficiency. Hence, this paper introduces a novel model for the composite transportation network design problem (CTNDP). Specifically, the model is designed to inform the planning of composite transportation networks by considering travel behaviors of land-air coordinated mobility. This innovative model is formulated as a bi-level programming problem, in which the upper-level model focuses on strategically planning vertiport locations and capacities, thereby reducing the total travel time within the transportation system. Upon determining decisions at the upper level, the composite transportation network can be established by constructing new links that interconnect the vertiports and existing road networks. The lower-level model addresses the land-air collaboration network equilibrium (LAC-NE) problem through mathematical programming. To solve the bi-level programming problem, a customized Bayesian optimization method, namely the mixed-integer Bayesian optimization (MI-BO) method, is proposed. Specifically, MI-BO is developed by incorporating the branch-and-bound algorithm into the Bayesian optimization framework. Additionally, an advanced path-based improved gradient projection (IGP) algorithm is developed to efficiently resolve the LAC-NE problem. The efficacy of the proposed model and solution algorithms are substantiated through numerical experiments, and the results illustrate the impact of land-air coordinated operations on the performance of the composite transportation network.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104967"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095590","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":"Integrated demand-oriented and energy-efficiency train timetabling and rolling stock circulation planning for an urban rail transit line","authors":"Yu Huang,&nbsp;Wenliang Zhou,&nbsp;Guangming Xu,&nbsp;Lianbo Deng","doi":"10.1016/j.trc.2024.104993","DOIUrl":"10.1016/j.trc.2024.104993","url":null,"abstract":"<div><div>Saving energy has both significant environmental benefits and economic advantages. As the urban rail transit network and its consumed energy continue to expand, it is crucial to optimize the energy-saving operation scheme of trains. Energy-saving train operation often requires longer section running times, which is obviously not conducive to the quality of passenger service. In order to ensure passenger service quality when pursuing the decrease of the train’s energy consumption and rolling stocks’ operation cost, this paper proposes an integrated optimization model of the demand-oriented and energy-efficiency train timetable and rolling stock circulation plan for urban rail transit. Its objective is to minimize train net energy consumption, rolling stock utilization cost, as well as passenger waiting time and travel time. Specifically, the net energy consumption is defined as the difference between train required traction energy consumption and regenerative braking energy utilization. To efficiently solve this large-scale mixed integer nonlinear model, we design a solution algorithm combining Variable Neighborhood Search (VNS) and CPLEX, in which seven different neighborhood structures are constructed. Based on the data of Guangzhou Metro Line 13, we have verified the effectiveness and performance of the model and algorithm through numerical experiments of various scales, as well as through comparisons with other algorithms and models. The results demonstrate that the timetable and rolling stock circulation plan obtained by VNS can reduce net energy consumption by 9.55 %, rolling stock utilization cost by 9 %, and passenger waiting time by 4.77 %, and their travel time by 0.87 % compared to the current timetable.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104993"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096023","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":"Estimating MFD model parameters from sparse license plate recognition data: The role of path reconstruction and regionalization","authors":"Cheng Hu ,&nbsp;Jinjun Tang ,&nbsp;Zhitao Li ,&nbsp;Yaopeng Wang ,&nbsp;Chuyun Zhao ,&nbsp;Jiguang Chen ,&nbsp;Hao Zhou","doi":"10.1016/j.trc.2024.104982","DOIUrl":"10.1016/j.trc.2024.104982","url":null,"abstract":"<div><div>The Macroscopic Fundamental Diagram (MFD) provides a convenient and computationally efficient tool for urban traffic monitoring and control. However, the accurate estimation of the model parameters is a prerequisite for the MFD models to be practically applicable. The significant deficiencies in commonly used data sources underscore the importance of utilizing new data sources to estimate the MFD model parameters. This study proposes a comprehensive framework to estimate critical parameters for multi-region MFD models based solely on License Plate Recognition (LPR) data. An efficient link-based path reconstruction algorithm is introduced to transform observed vehicle trajectories into continuous paths. Considering the inherent incompleteness of observed trajectories, this study presents a novel regionalization framework to match initial or final observation points to specific subregional networks. An adaptive large neighborhood search (ALNS) algorithm is proposed to improve the flow correlation within these subregions. Subsequently, an OD inference model using importance sampling is introduced to estimate the true OD of trips within the identified subregions. The resulting complete vehicle trips can be used to estimate trip length distributions and path flow coefficients. In addition, a method for estimating the MFD shape, tailored for application to sparse LPR data and based on reconstructed vehicle trajectories, is proposed. The effectiveness of these methods is validated through both simulation experiments and empirical studies. This framework is expected to facilitate the practical application of MFD models to realistic road networks.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104982"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096049","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 strategy in the collaborative urban freight transport system with concept of capacity allocation","authors":"Xin Guo ,&nbsp;David Z.W. Wang ,&nbsp;Huijin Sun ,&nbsp;Jianjun Wu ,&nbsp;Jin Zhou","doi":"10.1016/j.trc.2024.104973","DOIUrl":"10.1016/j.trc.2024.104973","url":null,"abstract":"<div><div>Worldwide, urban freight transport demand has rapidly expanded. Collaborative freight transport service, which integrates existing public transport system into the freight transport service, would be a promising solution to solve such post-pandemic urban freight transport problem. While most of the previous research works on this topic considered the operation of the public transport service and freight delivery service separately, this paper would focus on how to determine coordinated operational strategies of the participating public transport and freight transport services in a cooperative regime. Specifically, the definition of the capacity allocation event is proposed to encourage more seamless freight movements at transfer hubs within the given limited temporal restrictions while considering both the travel delay for public transport passengers and all incurred operational costs for offering the collaborative freight transport service. To this end, we propose a multi-objective mathematical model to describe the operation design of the collaborative freight transport service, aiming to maximize the synchronized freight movement at transfer hub and minimize the incurred passenger travel delay and operational costs. A Multi-objective Bernstein Basis Differential Evolution (MOBDE) solution method, requiring no pre-determined control parameters, is employed to find the optimal solution efficiently. Finally, an illustrative example is presented to demonstrate the validity of the model formulation and efficiency of the solution method for the operation design of collaborative freight transport services.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104973"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096501","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":"Event-based models for the electric autonomous dial-a-ride problem","authors":"Verena Stallhofer,&nbsp;Sophie N. Parragh","doi":"10.1016/j.trc.2024.104896","DOIUrl":"10.1016/j.trc.2024.104896","url":null,"abstract":"<div><div>On-demand transportation systems can serve to complement standard scheduled public transport in areas with low population density or to address the mobility needs of handicapped and elderly people. In this paper, we address the electric autonomous dial-a-ride problem (e-ADARP). In the e-ADARP, vehicle routes for serving user requests consisting of pickup and drop-off locations are determined. The objective is to minimize a weighted combination of travel distances and excess user ride time. Since it is assumed that an electric and autonomous vehicle fleet is used for the ride-sharing service, in addition to vehicle capacity, time windows, and maximum user ride times, also battery capacity constraints have to respected. We develop a mixed-integer linear programming (MILP) model for the e-ADARP that relies on an event-based graph. By using an event-based graph, capacity, pairing, and precedence constraints are implicitly applied. Several valid inequalities from the literature as well as newly developed ones are used to strengthen the model. In comparison to existing exact methods for the e-ADARP, we obtain competitive results on a set of available benchmark instances: we provide several improved upper and lower bounds and provide optimal solutions to previously unsolved instances. Furthermore, we analyze the impact of the capacity setting as well as different weight combinations on solution time and demonstrate the effect of battery start and end levels over several periods.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"171 ","pages":"Article 104896"},"PeriodicalIF":7.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095589","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}