Safety of the express freight train running over a long-span bridge

Purpose-Express freight transportation is in rapid development currently.Owing to the higher speed of express freight train,the deformation of the bridge deck worsens the railway line condition under the action of wind and train moving load when the train runs over a long-span bridge.Besides,the blunt car body of vehicle has poor aerodynamic characteristics,bringing a greater challenge on the running stability in the crosswind.Design/methodology/approach-In this study,the aerodynamic force coefficients of express freight vehicles on the bridge are measured by scale model wind tunnel test.The dynamic model of the train-long-span steel truss bridge coupling system is established,and the dynamic response as well as the running safety of vehicle are evaluated.Findings-The results show that wind speed has a significant influence on running safety,which is mainly reflected in the over-limitation of wheel unloading rate.The wind speed limit decreases with train speed,and it reduces to 18.83 m/s when the train speed is 160 km/h.Originality/value-This study deepens the theoretical understanding of the interaction between vehicles and bridges and proposes new methods for analyzing similar engineering problems.It also provides a new theoretical basis for the safety assessment of express freight trains.

Choosing Multimodal Freight Mix: An Integrated Multi-Objective Multicriteria Approach

Multimodal freight transportation emerges as the go-to strategy for cost-effectively and sustainably moving goods over long distances. In a multimodal freight system, where a single contract includes various transportation methods, businesses aiming for economic success must make well-informed decisions about which modes of transport to use. These decisions prioritize secure deliveries, competitive cost advantages, and the minimization of environmental footprints associated with transportation-related pollution. Within the dynamic landscape of logistics innovation, various multicriteria decision-making (MCDM) approaches empower businesses to evaluate freight transport options thoroughly. In this study, we utilize a case study to demonstrate the application of the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) algorithm for MCDM decision-making in freight mode selection. We further enhance the TOPSIS framework by integrating the entropy weight coefficient method. This enhancement aids in assigning precise weights to each criterion involved in mode selection, leading to a more reliable decision-making process. The proposed model provides cost-effective and timely deliveries, minimizing environmental footprint and meeting consumers’ needs. Our findings reveal that freight carbon footprint is the primary concern, followed by freight cost, time sensitivity, and service reliability. The study identifies the combination of Rail/Truck as the ideal mode of transport and containers in flat cars (COFC) as the next best option for the selected case. The proposed algorithm, incorporating the enhanced TOPSIS framework, benefits companies navigating the complexities of multimodal transport. It empowers making more strategic and informed transportation decisions. This demonstration will be increasingly valuable as companies navigate the ever-growing trade within the global supply chains.

Urban Freight Consolidation Model for Post-Hauler Planning

Freight transportation in urban areas has increased significantly in a shorter period due to the widespread use of e-commerce, fast delivery, and population growth. Recently, a noticeable government initiative aimed at creating an effective, acceptable, and sustainable city logistics policy. This paper examines freight consolidation as a transportation strategy for optimizing last-mile delivery costs. Freight consolidation involves combining smaller shipments from various origins into a single, larger shipment for more efficient transportation to a common destination. This approach is particularly beneficial for last-mile delivery, where frequent deliveries of smaller quantities are frequently visible. Finally, we provide an illustrative example targeting urban freight stakeholders for practicing possible consolidation methodology. The result in the illustrative example shows that freight with 3-day consolidation, despite the delay penalty, is cheaper than daily shipping, and both are cheaper than 2-day consolidated shipping. The study will benefit urban businesses and freight services.

Braking distance prediction for vehicle consist in low-speed on-sight operation:a Monte Carlo approach

The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive(e.g. in the case of depot operations) or highly inefficient(e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for lowspeed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.

Making Data-Driven Transportation Decisions for Freight Operations

Using Louisiana’s Interstate system, this paper aims to demonstrate how data can be used to evaluate freight movement reliability, economy, and safety of truck freight operations to improve decision-making. Data mainly from the National Performance Management Research Data Set (NPMRDS) and the Louisiana Crash Database were used to analyze Truck Travel Time Reliability Index, commercial vehicle User Delay Costs, and commercial vehicle safety. The results indicate that while Louisiana’s Interstate system remained reliable over the years, some segments were found to be unreliable, which were annually less than 12% of the state’s Interstate system mileage. The User Delay Costs by commercial vehicles on these unreliable segments were, on average, 65.45% of the User Delay Cost by all vehicles on the Interstate highway system between 2016 and 2019, 53.10% between 2020 and 2021, and 70.36% in 2022, which are considerably high. These disproportionate ratios indicate the economic impact of the unreliability of the Interstate system on commercial vehicle operations. Additionally, though the annual crash frequencies remained relatively constant, an increasing proportion of commercial vehicles are involved in crashes, with segments (mileposts) that have high crash frequencies seeming to correspond with locations with recurring congestion on the Interstate highway system. The study highlights the potential of using data to identify areas that need improvement in transportation systems to support better decision-making.

Accessibility Measures in Modal Choice Models: A Proof of Concept Applied to Freight Transport

Modal choice models applied to interregional or international freight transportation network models are often based on rather coarse origin-destination matrices, containing annual transported tonnages between (sub)regions, for instance. Generally, only basic (sometimes constructed) independent variables (transportation costs or transit times) are used because other variables such as shipment sizes, service frequencies, etc. are not available. Using origin-destination matrices and an assignment model, it is also possible to compute spatial accessibility measures that can further be used as additional explanatory variables. Indeed, several published studies have identified network accessibility as an important element in the mode-choice decision. This paper also shows that the inclusion of an accessibility measure in the utility functions of a logit model substantially improves the performance of a transportation network model, both in the modal choice and the assignment levels of the classical four-step model. Consequently, the assignment of the estimated modal demands results in more accurate estimated traffic on the networks. The model presented in this paper is to be considered as a proof of concept because its workflow should further be streamlined to make it easily useable by modelers.

面向入境货运业务的口岸疫情防控实践:以浦东国际机场为例

新型冠状病毒肺炎疫情发生以来,在“保供保生产”的防疫需求下,我国空港口岸的入境货运量不降反增,入境货运业务成为当前口岸疫情防控的重点内容之一,各口岸机场的先进实践经验需进一步总结与推广。基于浦东国际机场国际入境货运业务的探索实践,总结出以风险评估与流程再造为主的空港口岸货运疫情管控理论:包括“人、物、环境”同防策略下的货运要素风险评估方法、“风险对象分离原则”和“风险单元最小化原则”;明确基于风险分级的货运流程分类管理策略,提出货物动线设计、货物分离和拆装存运的方案;总结基于风险评估的货运人员动态管理方法与风险单元最小化的实践案例,涵盖机组边检、登记进出、健康监测、就医管理、住宿通勤等方面,为我国口岸货运业务疫情防控的精细化管理提供经验参考。

International Freight Forwarding Services Network in the Yangtze River Delta, 2005–2015: Patterns and Mechanisms

This study examined the spatio-temporal trajectories of the international freight forwarding service(IFFS) in the Yangtze River Delta(YRD) and explored the driving mechanisms of the service. Based on a bipartite network projection from an IFFS firm-city data source, we mapped three IFFS networks in the YRD in 2005, 2010, and 2015. A range of statistical indicators were used to explore changes in the spatial patterns of the three networks. The underlying influence of marketization, globalization, decentralization, and integration was then explored. It was found that the connections between Shanghai and other nodal cities formed the backbones of these networks. The effects of a city's administrative level and provincial administrative borders were generally obvious. We found several specific spatial patterns associated with IFFS. For example, the four non-administrative centers of Ningbo, Suzhou, Lianyungang, and Nantong were the most connected cities and played the role of gateway cities. Furthermore, remarkable regional equalities were found regarding a city's IFFS network provision, with notable examples in the weakly connected areas of northern Jiangsu and southwestern Zhejiang. Finally, an analysis of the driving mechanisms demonstrated that IFFS network changes were highly sensitive to the influences of marketization and globalization, while regional integration played a lesser role in driving changes in IFFS networks.

Numerical optimisation and experimental validation of divided rail freight brake disc crown

In this study, numerical optimisation and experimental validation of a divided rail freight brake disc crown made of grey cast iron EN-GJL-250 is presented.The analysed brake disc is used in rail freight wagons and possesses a load capacity of 22.5 tons per axle. Two of the divided rail freight brake discs are mounted on each axle.With the aid of numerical analysis, the thermal dissipation properties of the brake disc were optimised and ventilation losses were reduced, and the numerical results were compared with experimental results. A one-way fluid–structure interaction analysis was performed. A computational fluid dynamic model of a divided rail freight brake disc, used to predict air flow properties and heat convection, was incorporated into a finite element model of the disc and used to evaluate the temperature of the disc. A numerical parametrical optimisation of cooling ribs of the brake disc was also performed, and novel optimised cooling ribs were developed. A transient thermal numerical analysis of the brake disc was validated using temperature measurements obtained during a braking test on a test bench. The ventilation losses of the brake disc were measured on a test bench specifically designed for the task, and the losses were compared to the simulation results. The experimentally obtained ventilation losses and temperature measurements compared favourably with the simulation results, confirming that this type of simulation process may be confidently applied in the future. Through systematic optimisation of the divided rail freight brake disc, ventilation losses were reduced by 37% and the mass was reduced by 21%, resulting in better thermal performance that will bring with it substantial energy savings.

A dynamic model for railway freight overbooking

In order to apply overbooking idea in Chinese railway freight industry to improve revenue, a Markov decision process(dynamic programming) model for railway freight reservation was formulated and the overbooking limit level was proposed as a control policy. However, computing the dynamic programming treatment needs six nested loops and this will be burdensome for real-world problems. To break through the calculation limit, the properties of value function were analyzed and the overbooking protection level was proposed to reduce the calculating quantity. The simulation experiments show that the overbooking protection level for the lower-fare class is higher than that for the higher-fare class, so the overbooking strategy is nested by fare class. Besides, by analyzing the influence on the overbooking strategy of freight arrival probability and cancellation probability, the proposed approach is efficient and also has a good application prospect in reality. Also, compared with the existing reservation(FCFS), the overbooking strategy performs better in the fields of vacancy reduction and revenue improvement.

Novel integration of extreme learning machine and improved Harris hawks optimization with particle swarm optimization-based mutation for predicting soil consolidation parameter

The study proposes an improved Harris hawks optimization(IHHO) algorithm by integrating the standard Harris hawks optimization(HHO) algorithm and mutation-based search mechanism for developing a high-performance machine learning solution for predicting soil compression index. HHO is a newly introduced meta-heuristic optimization algorithm(MOA) used to solve continuous search problems.Compared to the original HHO, the proposed IHHO can evade trapping in local optima, which in turn raises the search capabilities and enhances the search mechanism relying on mutation. Subsequently, a novel meta-heuristic-based soft computing technique called ELM-IHHO was established by integrating IHHO and extreme learning machine(ELM) to estimate soil compression index. A sum of 688 consolidation test data was collected for this purpose from an ongoing dedicated freight corridor railway project. To evaluate the generalization capability of the proposed ELM-IHHO model, a detailed comparison between ELM-IHHO and other well-established MOAs, such as particle swarm optimization,genetic algorithm, and biogeography-based optimization integrated with ELM, was performed. Based on the outcomes, the ELM-IHHO model exhibits superior performance over the other MOAs in predicting soil compression index.

Forecasting Baltic Dirty Tanker Index by Applying Wavelet Neural Networks

Baltic Exchange Dirty Tanker Index (BDTI) is an important assessment index in world dirty tanker shipping industry. Actors in the industry sector can gain numerous benefits from accurate forecasting of the BDTI. However, limitations exist in traditional stochastic and econometric explanation modeling techniques used in freight rate forecasting. At the same time research in shipping index forecasting e.g. BDTI applying artificial intelligent techniques is scarce. This analyses the possibilities to forecast the BDTI by applying Wavelet Neural Networks (WNN). Firstly, the characteristics of traditional and artificial intelligent forecasting techniques are discussed and rationales for choosing WNN are explained. Secondly, the components and features of BDTI will be explicated. After that, the authors delve the determinants and influencing factors behind fluctuations of the BDTI in order to set inputs for WNN forecasting model. The paper examines non-linearity and non-stationary features of the BDTI and elaborates WNN model building procedures. Finally, the comparison of forecasting performance between WNN and ARIMA time series models show that WNN has better forecasting accuracy than traditionally used modeling techniques.

Intermodal Freight Network Design for Transport of Perishable Products

The amount of perishable products transported via the existing intermodal freight networks has significantly increased over the last years. Perishable products tend to decay due to a wide range of external factors. Supply chain operations mismanagement causes waste of substantial volumes of perishable products every year. The heretofore proposed mathematical models optimize certain supply chain processes and reduce decay of perishable products, but primarily deal with local production, inventory, distribution, and retailing of perishable products. However, significant quantities of perishable products are delivered from different continents, which shall increase the total transportation time and decay potential of perishable products as compared to local deliveries. This paper proposes a novel optimization model to design the intermodal freight network for both local and long-haul deliveries of perishable products. The objective of the model aims to minimize the total cost associated with transportation and decay of perishable products. A set of piecewise approximations are applied to linearize the non-linear decay function for each perishable product type. CPLEX is used to solve the problem. Comprehensive numerical experiments are conducted using the intermodal freight network for import of the seafood perishable products to the United States to draw important managerial insights. Results demonstrate that increasing product decay cost may significantly change the design of intermodal freight network for transport of perishable products, cause modal shifts and affect the total transportation time and associated costs.

Forecasting freight volume based on wavelet denoising and FG-Markov

To eliminate the grey bias and improve ant-jamming performance of the standard grey-Markov forecasting model,a forecasting model based on wavelet packet decomposition and fuzzy grey Markov(FG-Markov)is proposed considering the characteristics of randomness and nonlinearility of freight volume forecasting.Firstly,based on the data analysis ability of wavelet packet to non-stationary random signal,wavelet packet decomposition is used to improve the analysis ability of data signal by decomposing historical freight volume data into wavelet packet component.On this basis,FG-Markov chain is proposed to obtain the transfer probability matrix of wavelet packet coefficients by introducing fuzzy grey variables,and forecast the freight volume by reconstructing wavelet packet coefficients.Finally,an example of Lanzhou railroad hub is carried out in order to testify the validity and applicability of this forecasting model.Compared with neural network model and other forecasting models,the proposed forecasting model can improve the forecasting accuracy under the same conditions.The forecasting accuracy of wavelet packet decomposition and FG-Markov is not only greater than that of any other single forecasting models,but also superior to that of other traditional combinational forecasting models,which can meet the actual requirements of freight volume forecasting.

A Delivery Approach Modeling for Urban Freight Restocking

This paper proposes a modeling system developed in order to analyze the urban freight transport and logistics within urban and metropolitan areas. A review of models developed to simulate this segment of mobility is also reported. The review analysis highlights the limits of models for the ex-ante assessment of city logistics measures. For this reason this paper proposes a new modeling system approach for the assessment of city logistics measures. It is made of different steps approaching problems related to quantity OD （Origin-Destination） flows, restocking type OD flows, delivery OD flows, delivery OD flows for time slice and vehicle type, and vehicle OD flows. This modeling system has been specified and calibrated using some surveys carried out in the inner area of Rome where more than 500 truck drivers and more than 600 retailers have been interviewed.

Freight Vehicle Routing Optimization for Sporadic Orders Using Floating Car Data

The increasing popularity of e-commerce brings large volumes of sporadic orders from different customers,which have to be handled by freight trucks and distribution centers. To improve the level of service and reduce the total shipping cost as well as traffic congestions in urban area, flexible methods and optimal vehicle routing strategies should be adopted to improve the efficiency of distribution effort. An optimization solution for vehicle routing and scheduling problem with time window for sporadic orders (VRPTW- S) was provided based on time-dependent travel time extracted from floating car data (FCD) with ArcGIS platform. A VRPTW-S model derived from the traditional vehicle routing problem was proposed, in which uncertainty of customer orders and travel time were considered. Based on this model, an advanced vehicle routing algorithm was designed to solve the problem. A case study of Shenzhen, Guangdong province, China, was conducted to demonstrate the vehicle operation flow,in which process of FCD and efficiency of delivery systems under different situations were discussed. The final results demonstrated a good performance of application of time-dependent travel time information using FCD in solving vehicle routing problems.

A Freight Mode Choice Analysis Using a Binary Logit Model and GIS: The Case of Cereal Grains Transportation in the United States

Mode choice is important in shipping commodities efficiently. This paper develops a binary logit model and a regression model to study the cereal grains movement by truck and rail in the United States using the publically available Freight Analysis Framework (FAF2.2) database and U.S. highway and networks and TransCAD, a geographic information system with strong transportation modeling capabilities. The binary logit model and the regression model both use the same set of generic variables, including mode split probability, commodity weight, value, network travel time, and fuel cost. The results show that both the binary logit and regression models perform well for cereal grains transportation in the United States, with the binary logit model yielding overall better estimates with respect to the observed truck and rail mode splits. The two models can be used to study other commodities between two modes and may produce better results if more mode specific variables are used.

The Effects of Freight Vibrations on Slope Stability along the SH35, Bay of Plenty East, New Zealand

State Highway 35 (SH35) connects Opotiki to Gisborne along the Raukumara Peninsula in the North Island, New Zealand. This corridor passes through an area which is prone to landslides, especially during the wet season. This, in turn, influences the traffic and has detrimental effects to the local economy, as it is dependent mainly on tourism and commercial transportation by road. This paper will focus on the landslides which occurred between June and September 2018, within the Bay of Plenty East on the north side of the Raukumara Peninsula. The paper will analyze both the nature and triggering mechanisms behind these landslides. As the landslides occur in the wet season, rainfall has been commonly considered the main trigger. However, the paper will argue that vehicle vibrations have been contributing to the instability of the slopes within the Bay of Plenty East. This paper will be instrumental in developing future transportation strategies in this part of the North Island.

Factors Analysis of Affecting Loading and Reinforcing Scheme of Large Goods in Railway

Large goods transported in railway are kinds of special goods and they are very important in national construction. In order to transport safely, loading and reinforcing schemes must be made first. How to design a reasonable scheme will be affected by many factors. This paper presents the characteristic of the large goods, summarizes the process of designing a loading and reinforcing scheme of large good, then probes the factors of affecting the loading and reinforcing scheme and gives a detail analysis. It’s considered that those out-of-gauge and overweight degree of goods, center-of- gravity height of a loaded wagon, position of center-of-gravity of goods, type of wagon for using, reinforcement material and reinforcement method, transport expense and transport organization could affect a scheme in the aspects of safety, economy, rapidity and convenience. This conclusion will instruct and help to make a good scheme.

Research on Optimization of Freight Train ATO Based on Elite Competition Multi-Objective Particle Swarm Optimization

In view of the complex problems that freight train ATO (automatic train operation) needs to comprehensively consider punctuality, energy saving and safety, a dynamics model of the freight train operation process is established based on the safety and the freight train dynamics model in the process of its operation. The algorithm of combining elite competition strategy with multi-objective particle swarm optimization technology is introduced, and the winning particles are obtained through the competition between two elite particles to guide the update of other particles, so as to balance the convergence and distribution of multi-objective particle swarm optimization. The performance comparison experimental results verify the superiority of the proposed algorithm. The simulation experiments of the actual line verify the feasibility of the model and the effectiveness of the proposed algorithm.