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Robust and Trustworthy data Sharing Framework Leveraging On-Chain and Off-Chain Collaboration

Computers, Materials & Continua 2024年第2期78卷 2159-2179页

作者： Jinyang Yu Xiao Zhang Jinjiang Wang Yuchen Zhang Yulong Shi Linxuan Su Leijie Zeng School of Computer Science Northwestern Polytechnical UniversityXi’an710072China MIIT Key Laboratory of Big Data Storage and Management Northwestern Polytechnical UniversityXi’an710072China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Northwestern Polytechnical UniversityXi’an710072China

The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy *** distributed storage systems are hindered by centralized management and lack traceability,while blockchain systems are limited by low capacity and high *** address these challenges,the present study investigates the reliable storage and trustworthy sharing of IoT data,and presents a novel system architecture that integrates on-chain and off-chain data manage *** architecture,integrating blockchain and distributed storage technologies,provides high-capacity,high-performance,traceable,and verifiable data storage and *** on-chain system,built on Hyperledger Fabric,manages metadata,verification data,and permission information of the raw *** off-chain system,implemented using IPFS Cluster,ensures the reliable storage and efficient access to massive files.A collaborative storage server is designed to integrate on-chain and off-chain operation interfaces,facilitating comprehensive data *** provide a unified access interface for user-friendly system *** testing validates the system’s reliability and stable *** proposed approach significantly enhances storage capacity compared to standalone blockchain *** reliability tests consistently yield positive *** average upload and download throughputs of roughly 20 and 30 MB/s,respectively,the system’s throughput surpasses the blockchain system by a factor of 4 to 18.

关键词： On-chain and off-chain collaboration blockchain distributed storage system hyperledger fabric IPFS cluster

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Optimal Scheduling of Single-Line Electric Buses with Battery Swapping 8

Optimal Scheduling of Single-Line Electric Buses with Batter...

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8th IEEE International Conference on Intelligent transportation engineering, ICITE 2023

作者： Guo, Yuyan Liu, Tao Institute of System Science and Engineering School of Transportation and Logistics Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9798350314212

With the advantages of zero emission and comfortable riding experience, battery-electric buses (BEBs) are widely adopted in public transit agencies as a green alternative to conventional diesel buses. Battery swapping technology is an efficient and promising charging technology to address the issues of battery range anxiety and long battery charging time. This study developed a two-stage optimization model to optimize the single-line battery-electric bus scheduling problem considering battery swapping. At the first stage, a bi-objective integer programming model is established to determine the minimum BEB fleet size, together with the BEB-to-trip assignment and battery swapping schedule. At the second stage, an integer linear programming model is formulated to determine the required minimum number of batteries. An e-constraint method is designed to investigate the trade-off between the required minimum fleet size and the number of back-up batteries. Finally, a real-world case study of a BEB line in Chengdu, China, is conducted to demonstrate the effectiveness of the optimization model and solution method. Sensitivity analyses are further conducted to understand the impacts of some key parameters, including battery capacity, number of trips, cycle time, and battery swapping time. The results show that battery capacity and cycle time have significant influences on BEB-to-trip assignment results and battery swapping schedule. © 2023 IEEE.

关键词： Sensitivity analysis

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Research on Equipment Management System of Railway Passenger Station Based on High-Precision Positioning 5th

Research on Equipment Management System of Railway Passenger...

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5th International Conference on Smart Vehicular technology, transportation, Communication and applications, VTCA 2022

作者： Li, Lexi Wang, Bozhou Liu, Zhen Ni, Shaoquan School of Transportation and Logistics Southwest Jiaotong University Sichuan Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest Jiaotong University Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu610031 China

ISBN: (纸本)9789819908479

The equipment management informatization and intelligentization in railway passenger stations is a significant component of the construction of intelligent stations. The current equipment management of railway passenger stations is slowly developing and backward in its approach. This paper studied the weaknesses of equipment management in railway passenger stations, conducted demand analysis, and proposed the development direction of equipment management in railway passenger stations with the support of theoretical basis and technical basis. The technical architecture of the high-precision positioning-based railway passenger station equipment management system was built from the terminal layer, application layer, service layer, data layer and perception layer, and four functional modules were designed for equipment management: equipment real-time dynamic trackment, full life-cycle management, equipment fault responsibility traceability, and incident response. The key technologies required for the construction of the system were studied, including Bayesian fusion-based equipment positioning technology with high accuracy and neural network-based remaining life prediction technology. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Informatization

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Distribution Vehicle Routing Optimization Based on 3D Loading 4th

Distribution Vehicle Routing Optimization Based on 3D Loadin...

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4th International Conference on Smart Vehicular technology, transportation, Communication and applications, VTCA 2021

作者： Luo, Xuan Zhang, Jin Yin, Tingyu Zhu, Hongxing Qiu, Mingyue School of Transportation and Logistics Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Comprehensive Transportation Big Data Application Technology Laboratory Chengdu611756 China

ISBN: (纸本)9789811640384

The rapid development of e-commerce leads to increasingly fierce competition in the logistics industry. Cost reduction and efficiency has become the key issue for logistics enterprises to survive. Loading optimization and path optimization are the two core issues in distribution activities, and they are inseparable and related. The joint optimization of the two is more in line with the actual distribution optimization needs. Based on the analysis of the interaction between routing and loading, this paper proposes a multi-objective optimization model with the minimum distribution cost, the minimum number of vehicles and the maximum customer satisfaction as the objectives. A hybrid nesting algorithm based on NSGAII algorithm is designed, in which the packing module is designed by tree search algorithm combined with the deepest and leftmost algorithm. Finally, the real data of China Railway Express Chengdu branch are taken as a case to verify the feasibility of the model and algorithm. Combined with the results of the algorithm, some suggestions are put forward. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Customer satisfaction

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Travel Activity Characteristics Identification Based on Driving Trajectory data 24

Travel Activity Characteristics Identification Based on Driv...

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24th COTA International Conference of transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal transportation, CICTP 2024

作者： Xie, Kun Xing, Xinyuan Dong, Honghui Dong, Chunjiao Ma, Jihui Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport School of Traffic and Transportation Beijing Jiaotong Univ. Beijing China College of Transportation Engineering Tongji Univ. Shanghai China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

Residence and work place are the most frequent places in all the starting and ending points of residents’ travel. The commuting trip with residence as the starting and ending point has a high regularity, which is an important travel feature of residents. Based on the GPS data of travel trajectory, this paper establishes an important stop identification method based on the clustering algorithm of mean shift, and a work residence identification method based on the double constraints of time and space, so as to identify important places of residence and work in travel activities. The research results can be described as accurate identification of residents’ occupational residence and excavation of the spatial and temporal distribution of residents’ occupational residence to provide data support for urban occupational residence planning, public resource allocation, and traffic management decisions. © ASCE.

关键词： Resource allocation

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Multimodal or intermodal: greenhouse gas emissions in less than container load in China–Pakistan trade

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Environment Systems and Decisions 2023年第2期43卷 265-280页

作者： Shoukat, Rizwan School of Transportation and Logistics Southwest Jiaotong University Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China Lab of National United Engineering Laboratory of Integrated and Intelligent Transportation No. 111 North Second Ring Road Chengdu China

The most important factors to consider in transportation are the items being transported, the origin and destination locations, the length of the trip, the mode of transportation required (truck, train, plane, or ship), the shipping due dates, the costs, the level of security, regulation, and monitoring, and the costs. Specifically, the goal of this study is to determine the cost of, delivery time for, and greenhouse gas (GHG) emissions related to the import of less than container load (LCL) from China to Pakistan. For the multiobjective problem, we employed the mixed-integer linear programming (MILP) approach to construct it while keeping the supply and demand constraints in mind. We tackled the problem using a multiobjective evolutionary algorithm and developed Pareto optimal solutions that could trade-off cost, time, and GHG emission in order to achieve the best possible result. According to the data, which was received from one of Pakistan’s top logistics service companies, using intermodal transportation to carry a ten-tonne product from Shanghai in China to Kasur in Pakistan will cost 37 per cent more, take 14 per cent longer, and emit more greenhouse gases than using traditional multimodal transportation. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Genetic algorithm GHG emission Intermodal transportation costs Less than container Multiobjective problem

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Research on Equipment Operation and Maintenance Management technology of Large Railway Passenger Station 5th

Research on Equipment Operation and Maintenance Management T...

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5th International Conference on Smart Vehicular technology, transportation, Communication and applications, VTCA 2022

作者： Wang, Bozhou Li, Lexi Ni, Shaoquan Chen, Dingjun School of Transportation and Logistics Southwest Jiaotong University Sichuan Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest Jiaotong University Sichuan Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Sichuan Chengdu610031 China

ISBN: (纸本)9789819908479

With the development of informationization and intelligence of railway passenger stations, problems such as inconvenient information interaction, missing operation and maintenance data, and difficulty in accurate positioning of equipment under the existing equipment operation and maintenance management mode have become the focus. In this paper, the operation and maintenance management process of equipment is divided into three stages: fault prediction and warning, fault diagnosis and processing, and fault rule summary. The implementation schemes of key technologies such as data warehouse, data mining, 5G fusion positioning, and electronic fence are given to realize functions such as condition assessment, fault prediction, fault diagnosis, precise positioning, fence warning, and auxiliary decision-making, which can meet the needs of managers and operations people. Research will help to improve the efficiency and safety of equipment operation and maintenance, and have a reference significance for integrated intelligent operation and maintenance technology and the construction of modern passenger stations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data mining

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Stability Analysis of Mixed Traffic Flow with Connected and Autonomous Vehicles Based on Simplified DSM Model 23

Stability Analysis of Mixed Traffic Flow with Connected and ...

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23rd COTA International Conference of transportation Professionals: Emerging data-Driven Sustainable Technological Innovation in transportation, CICTP 2023

作者： Long, Wenmin Lu, Guangquan Liu, Miaomiao Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang Univ. Beijing China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beihang Univ. Beijing China

ISBN: (数字)9780784485040

ISBN: (纸本)9780784485040

The applications of mobile communication and automatic driving-related technologies in transportation have made a revolution for us in traffic information perception, vehicle cooperative control, and traffic management. Besides, the emergence and development of connected vehicles (CV) and connected and autonomous vehicles (CAV) have gradually changed the traditional traffic flow into a mixed one. In order to investigate their influences and characteristics of mixed traffic flows, this paper constructs an analysis model to derive the linear stability condition of the mixed traffic flow with CV and CAV based on the simplified desired safety margin (SDSM) model. Several numerical experiments are conducted to analyze the string stability of homogeneous and heterogeneous traffic flow, respectively. The results reveal that the presence of CAV could contribute to improving the string stability as well as reducing rear-end crashes. The higher the penetration rate of CAV, the more stable the string. And the time delay in drivers and communications is not conducive to the string stability. Besides, it is also found that controllable vehicles show great potential in preventing shockwave formation and propagation, suggesting a new way in traffic flow management. © ASCE.

关键词： Cooperative communication

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A Cooperative Truck Platooning Approach on Ramp Merging Area of Highway in Mixed Traffic 7

A Cooperative Truck Platooning Approach on Ramp Merging Area...

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7th IEEE International Conference on transportation Information and Safety, ICTIS 2023

作者： Sang, Xiao Bai, Linhan Zhou, Tao Zheng, Fangfang School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu China Jiangsu Railway Group Nanjing China

ISBN: (纸本)9798350308532

Truck platooning has emerged as a promising solution for improving traffic efficiency on highways. This paper proposes an optimization model for connected automated trucks (CATs) that addresses the trajectory optimization problem for CATs as human-driven trucks (HDTs) merge onto highways from on-ramps in a mixed traffic scenario. To maximize the speed of the mixed traffic system, we propose a mixed integer programming (MIP) model based on a rolling horizon algorithm. The algorithm optimizes CATs' trajectories iteratively, taking into account real-time updates on their driving state, and guides HDTs to follow the trajectories of CATs. The numerical experiments demonstrate that the increasing number of HDTs on the on-ramp negatively impacts the overall system performance, leading to higher traffic delay and reduced system stability. Furthermore, accounting for the stochastic behavior of HDTs can lead to increased instability in the system. Finally, we show that the objective function that comprehensively considers the system speed and platooning time effectively minimizes the delay of all vehicles. © 2023 IEEE.

关键词： Trucks

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Fine-Grained Traffic Pollution Monitoring and Estimation: A Case Study in Chengdu 13th

Fine-Grained Traffic Pollution Monitoring and Estimation: A ...

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13th International Conference on Environmental Science and technology, ICEST 2022

作者： Peng, Xin Sun, Zhanbo Liu, Runzhe Yang, Feilong Southwest Jiaotong University Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China Panzhihua University Panzhihua China

ISBN: (纸本)9783031274305

Accurate, fine-grained monitoring and estimation of traffic pollution are essential for preventing people from the health issues caused by air pollution. In this paper, we illustrated the concept of conducting fine-grained spatial interpolation of near-road traffic pollution distribution with mobile monitoring data. Different spatial interpolation techniques, including Kriging, Natural Neighbor Tessellation (NNT), and Inverse Distance Weighted (IDW) were compared. Results show NNT outperforms others especially in the cases of sparse data. This conclusion contributes to the monitoring and estimation of traffic pollution in smart cities. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Kriging

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