Freight Volume Research Articles

Evaluation and Effectiveness of Reallocating Traffic Signal Timing at Corridors with High Freight Volume

The COVID-19 pandemic drastically altered traffic patterns across the globe. With more people staying at home and relying on delivery services, there was a reduction in passenger car traffic but an increase in freight traffic. This study investigates the changes in traffic volume and mode splits during the COVID-19 pandemic at the intersection of Broening Highway and Holabird Avenues and investigates traffic signal reallocation strategies that account for the changes in traffic. This study considers morning peak traffic volumes before and during COVID. A methodology was developed to evaluate and measure freight volumes and emissions. From the literature, the cost per kilogram of CO, VOC, and NOx was $5.85, $3,37, and $12.53, respectively. The intersection operated at a level of service (LOS) of C both pre-COVID and during COVID. Traffic volume decreased by 24.3% during COVID at the study location; car volumes declined by 50%, and truck volumes increased by 130%. The total rate of emissions decreased by 22.6%.

Ropax Short-Sea Shipping and Covid-19 Pandemic: Case of Finland

Traveling was constantly growing among European Union (EU) countries before Covid-19 pandemic. In many coastal regions, passenger and freight transportation were tied together with roll-on/roll-off passenger (ropax) ferries. However, since the pandemic started, the passenger side of ropax operations has been under numerous new restrictions, bans and requirements. These have changed rather much during the pandemic era in Finland, creating more distortion and profound volume loss. In 2020, governmental support mechanisms were implemented to avoid significant losses. Thus, freight transportation has sustained. In addition, some restructuring and changes of ropax ferry routes have taken place. Now ropax companies concentrate on shorter routes, and volumes are more devoted to certain seaports. However, the situation did not improve in 2021, and subsidies continued, revenues were barely growing, and profitability was limited. Regression models suggest that Covid-19 resulted in a loss of 14.9 mill. passengers and 1.178 bill. EUR as revenue, where unitized freight volumes were unaffected.

Green Building Efficiency and Influencing Factors of Transportation Infrastructure in China: Based on Three-Stage Super-Efficiency SBM–DEA and Tobit Models

As an important part of low-carbon ecological city construction, green building is also an objective requirement of sustainable development. Based on the green building panel data of 30 provincial administrative regions in China from 2010 to 2020, the super-efficiency SBM model combined with the three-stage DEA model was adopted to obtain the green building efficiency value that was closer to the real situation by excluding the influence of environmental factors and statistical noise. Green buildings in China have only been developing for just over ten years and are still in the initial stage of spatial aggregation in which transportation infrastructure plays an important role in scale effect. This manuscript focuses on analyzing the influence factors, intensity and direction of transportation infrastructure on green building efficiency. The results show that: (1) The agglomeration effect is obvious in the area of green buildings with high efficiency, but the radiation effect is not strong in low-efficiency area. (2) Municipal transportation infrastructure investment, road surface area, per capita number of stations and interregional traffic network density have a positive impact on green building efficiency, while freight volume has a negative impact.

Flow of goods to the shock of COVID-19 and toll-free highway policy: Evidence from logistics data in China

Using high-frequency logistics data from China, this paper quantitatively examines the negative impact of the COVID-19 pandemic on logistics. Meanwhile, our research focuses on the toll-free highway policy during the COVID-19 pandemic, analyzing the promoting effect of this policy on road freight in China. Three main conclusions are drawn from the study. Firstly, the COVID-19 pandemic led to an average daily drop of 0.67% in road freight volume and an increase of 0.48% in logistic cost compared to the pre-pandemic period. Secondly, the toll-free highway policy had a significant offset effect of pandemic on freight volume and price, stimulating the resumption of work and production. However, the dynamic effect shows that the toll-free highway policy is only temporarily effective rather than the long term. Thirdly, the effectiveness of the toll-free highway policy is moderated by the severity of the epidemic and the transportation distance. This paper contributes to research on economy recovery and transportation policy under the COVID-19 pandemic shock.

Evaluation of Port Logistics Efficiency and Analysis of Influencing Factors

This paper constructs a port logistics input-output index system of Chongqing port, and analyzes the port logistics efficiency and influencing factors of Chongqing port using DEA-BCC and Tobit models. The results show that the overall port logistics efficiency of Chongqing port shows an incremental increase due to the continuous improvement of pure technical efficiency and scale efficiency. Port logistics efficiency has reached DEA effective and accompanied by fluctuation in recent years. The study shows that port city GDP negatively affects technical efficiency and scale efficiency. Unit port berth output positively affects technical efficiency and pure technical efficiency. The level of urbanization positively affects technical efficiency and scale efficiency, while population size positively affects scale efficiency only. Road freight volume and rail freight volume do not have an impact on port logistics efficiency.

Ghana's railway transport services delivery: A review

Ghana's once vibrant railway system is presently in a state of disrepair as a result of neglect and underfunding over the years; from an initial network size of 947 km in 1960 to an operational rail line of just 160 km in 2020. The Ghana railway sector's past performance is reviewed together with 5 other countries, namely; Nigeria, Kenya, South Africa, Germany, and the United Kingdom, as well as the prospects of the industry to the Government's intention. Four (4) indicators were considered in the assessment, they are, the effectiveness of the available rail line, total goods transported by rail, total passengers that traveled by rail, and accessibility to rail service. Relatively, Ghana showed the highest decline in the effectiveness of available rail lines, from 68% in 1980 to 16.9% in 2020. Again, Ghana and Nigeria experienced a substantial decrease in freight volumes transported (81%) between 1990 and 2020, whiles South Africa, Germany, and the United Kingdom witnessed increases averaging 100,000 million ton-km annually over the same period. Accessibility to railway services has consistently decreased over the years; from service access of 29.6% in 1960 to 0.6% in 2020 tells the awful state of the railway sector. However, the prospects of investing in a modernized railway system appear good as the government's drive to industrialize the country continues and new mineral deposits are exploited. The sector is undergoing restructuring to increase private sector participation in the delivery of rail transport services and to stimulate the country's socio-economic development.

Image Classification of Parcel Boxes under the Underground Logistics System Using CNN MobileNet

Despite various economic crisis situations around the world, the courier and delivery service market continues to be revitalized. The parcel shipping volume in Korea is currently 3.37 billion parcels, achieving a growth rate of about 140% compared to 2012, and 70% of parcels are from metropolitan areas. Given the above statistics, this paper focused on the development of an underground logistics system (ULS), in order to conduct a study to handle the freight volume in a more eco-friendly manner in the center of metropolitan areas. In this paper we first analyzed the points at which parcel boxes were damaged, based on a ULS. After collecting image data of the parcel boxes, the damaged parcel boxes were detected and classified using computerized methods, in particular, a convolutional neural network (CNN), MobileNet. For image classification, Google Colaboratory notebook was used and 4882 images were collected for the experiment. Based on the collected dataset, when conducting the experiment, the accuracy, recall, and specificity of classification for the testing set were 84.6%, 82% and 88.54%, respectively,. To validate the usefulness of the MobileNet algorithm, additional experiments were performed under the same conditions using other algorithms, VGG16 and ResNet50. The results show that MobileNet is superior to other image classification models when comparing test time. Thus, in the future, MobileNet has the potential to be used for identifying damaged boxes, and could be used to ensure the reliability and safety of parcel boxes based on a ULS.

Freight volume forecast of China Railway Express based on ES-GA-BP with combined input

China Railway Express is an important support that promotes the Belt and Road Initiative. Scientific and reasonable forecast of the train demand is of great significance to the formulation of China Railway Express transportation scheme. Taking the forecast of freight volume of China Railway Express as an object, considering the fluctuation and influence factors, we propose a freight volume forecasting method based on exponential smoothing, genetic algorithm and optimized back propagation (ES-GA-BP) neural network with combined input. Firstly, we analyze the current status of China Railway Express freight transport, and select influencing factors with high correlation as the input of neural network. Then, the exponential smoothing method is used to fit and forecast the historical data of China Railway Express freight volume, so as to optimize the input of neural network. Genetic algorithm is used to optimize the parameters of back propagation neural network to further improve the prediction accuracy. Finally, the prediction of freight container numbers in the international transport channel of 'Hunan Europe Express' is taken as an example to verify the effectiveness of the method. The calculation results show that the combined input ES-GA-BP method is suitable for solving the problem of freight volume forecasting with large fluctuation, and the prediction accuracy is good, which is conducive to the formulation of a reasonable China Railway Express transportation scheme.

Forecasting of Freight Demand Transportation (Case Study in Lampung Province, Indonesia)

Forecasting the volume of freight has a significant importance for future decisions for the entire economy, as well as its individual participants. The transportation of goods between Sumatra and Java using the highway mode that accumulate with local transportation will greatly burden roads in Lampung province. This research was conducted to predict the pattern and amount of movement of goods in the future. The modelling is conducted for the plan period up to 20 years based on growth predictions of geographical, social, economic and traffic flow. This study conducted a process of Sequential Demand Model (Planning Model 4 stages) by using software Transplan Version 8. Transportation patterns in 2040 is predicted will be dominated by continuous trips with domination of movement from Java to South Sumatra, or otherwise. Both the transportation between internal zones and external zone to internal zone have a significant increase. The most strategic main line freight in Lampung for today and in the future is along the Bakauheni-South Sumatra and Bengkulu-South Sumatra both through toll roads, national roads, and railways.

Opportunities and Barriers for Truck Platooning on Norwegian Rural Freight Routes

Truck platooning can potentially make road freight transportation safer and greener. Technological readiness, business opportunities, and acceptance of truck platooning have mainly been studied for multilane highways with ample truck volumes. Less is known about truck platooning in areas with low traffic volumes and challenging roads and weather conditions. This paper investigates the opportunities and barriers for truck platooning on Norwegian rural freight routes, through stakeholder interviews and realistic case examples. Given modest freight volumes, dispersed industry clusters, and challenging road conditions, this study identified several prerequisites to deploying platooning and achieving economic savings. The paper discusses the future steps required to organize platooning across carriers, ensure appropriate infrastructure, and gain acceptance among truck drivers, motorists, and other road users.

Revisiting the marketing approach between seaports and dry ports in Malaysia: current trend and strategy for improvement

Purpose This paper aims to explore the comparative analysis of marketing strategies between seaports and dry ports. Second, this paper proposes a recommendation to improve marketing approaches in both nodes.Design/methodology/approach This research analyzes current marketing approaches to improve the freight volume and enhance interrelation between them for a comprehensive collaboration in the freight supply chain. This research employed semi-structured interviews via an e-interview questionnaire.Findings The result shows that dry port and seaport practice a mixed marketing strategy. Some marketing elements that a seaport applies are also applied by a dry port, like focusing on the target customer, joining exhibitions and face-to-face meetings. Customized service to clients, frequent discussion on the effective marketing plans and increasing the facilities at the seaport and dry ports can improve the marketing strategies in dry port and seaports.Originality/value Seaports are the critical components in esteem-driven context, which add to supply chains by creating value-added services in the transport chain. Nonetheless, research between dry ports and seaports has increasingly drawn the attention of scholars during the last decade. Having said like that, there have not been any pragmatic studies undertaken in the Malaysian context that mainly discusses the marketing prospect of the dry ports and seaports especially during COVID-19 outbreak.

Effects of Preparedness on Successful Emergency Response to Ship Accident Pollution Using a Bayesian Network

With the rapid development of international trade and the fast growth of port freight volumes, the risk of ship pollution in marine areas has significantly increased. Frequent ship pollution accidents seriously endanger marine ecosystems and are extremely unfavorable to economic development and marine environmental protection. In this study, we investigate the results of emergency responses after ship pollution accidents and analyze the factors affecting a successful emergency response. A Bayesian network model of the emergency response results of ship pollution is established, and the emergency response results of ship pollution accidents in the example of Zhoushan Port are analyzed. Based on the analysis, suggestions for strengthening the emergency preparedness of Zhoushan Port are proposed. We believe that the results of this are beneficial for improving ship pollution risk management and decision making, and that they have practical significance for marine environmental protection.

Uncoupling Molecular Testing for SARS-CoV-2 From International Supply Chains.

The rapid global rise of COVID-19 from late 2019 caught major manufacturers of RT-qPCR reagents by surprise and threw into sharp focus the heavy reliance of molecular diagnostic providers on a handful of reagent suppliers. In addition, lockdown and transport bans, necessarily imposed to contain disease spread, put pressure on global supply lines with freight volumes severely restricted. These issues were acutely felt in New Zealand, an island nation located at the end of most supply lines. This led New Zealand scientists to pose the hypothetical question: in a doomsday scenario where access to COVID-19 RT-qPCR reagents became unavailable, would New Zealand possess the expertise and infrastructure to make its own reagents onshore? In this work we describe a review of New Zealand's COVID-19 test requirements, bring together local experts and resources to make all reagents for the RT-qPCR process, and create a COVID-19 diagnostic assay referred to as HomeBrew (HB) RT-qPCR from onshore synthesized components. This one-step RT-qPCR assay was evaluated using clinical samples and shown to be comparable to a commercial COVID-19 assay. Through this work we show New Zealand has both the expertise and, with sufficient lead time and forward planning, infrastructure capacity to meet reagent supply challenges if they were ever to emerge.

Forecasting regional short-term freight volume using QPSO-LSTM algorithm from the perspective of the importance of spatial information.

It is of great significance to accurately and efficiently predict expressway freight volume to improving the supervision level of the transportation industry and reflect the performance of transportation. Using expressway toll system records to predict regional freight volume plays an important role in the development of expressway freight organization work; especially, the short-term (hour, daily or monthly) freight volume is directly related to the compilation of regional transportation plans. Artificial neural networks have been widely used in forecasting in various fields because of their unique structural characteristics and strong learning ability, among which the long short-term memory (LSTM) network is suitable for processing and predicting series with time interval attributes such as expressway freight volume data. Considering the factors affecting regional freight volume, the data set was reconstructed from the perspective of spatial importance; we then use a quantum particle swarm optimization (QPSO) algorithm to tune parameters for a conventional LSTM model. In order to verify the efficiency and practicability, we first selected the expressway toll collection system data of Jilin Province from January 2018 to June 2021, and then used database and statistical knowledge to construct the LSTM data set. In the end, we used a QPSO-LSTM algorithm to predict the freight volume at the future times (hour, daily or monthly). Compared with the conventional LSTM model without tuning, the results of four randomly selected grids naming Changchun City, Jilin city, Siping City and Nong'an County show that the QPSO-LSTM network model based on spatial importance has a better effect.

An empirical analysis of driving factors of Xi’an hub economic development

In order to promote Xi’an’s economic development as an export-oriented hub, 7 indicators, including GDP, foreign trade volume, investment volume, passenger transport volume, freight volume, post and telecommunications business income, and the number of industrial enterprises above designated size, are selected to analyze the development of the hub economy through multiple linear regression analysis method. The results show that foreign trade, passenger traffic and post and telecommunications business revenues are significant to the economic development of Xi’an hub. However, the freight volume, investment and the number of enterprises above designated size have not passed the inspection. According to self-organization theory, the countermeasures for Xi’an to develop the hub economy are puts forward.

Econometric analysis of cargo transportation in the EAEU: the results of the retrospective forecast

The article is devoted to the econometric analysis of the volume of freight traffic in the EAEU by three modes of transport: road, rail and air. Regression equations describing the dependence of freight traffic volumes on economic activity factors are constructed and investigated. All the studied equations showed high predictive accuracy, confirmed by the results of a retrospective forecast.

Логістична інфраструктура Тернопільської області

A study of the transport network of Ternopil region was conducted. The existing transport network for all types of transport operating in the region, in particular, railway, road, aviation, river, pipeline in terms of traffic volumes is analyzed. The dynamics of passenger traffic in the region by mode of transport in the period from 2016 to 2020 is analyzed and conclusions are drawn on its operation. An analysis of the volume of freight traffic in the Ternopil region by mode of transport in the period 2016-2020. The transport industry is characterized in terms of railway, automobile, aviation and pipeline complex in terms of the availability of fleet, stations, waiting rooms and other necessary infrastructure. The logistics infrastructure of Ternopil region is represented by rail, road, river, pipeline and air transport. The main factors that reflect the peculiarities of the formation of transport infrastructure of Ternopil region are as follows: 1. Location in the center of the Western region of Ukraine, as well as proximity to the borders with EU countries provides a unique economic and geographical position of the region. 2. Favorable physical-geographical and favorable natural and climatic conditions for the development of transport infrastructure (most of the region is a flat area, only in the north are the Kremenets Mountains). 3. Availability of the required amount of transport, warehousing infrastructure, communication lines and power lines. 4.The economic potential of the region contributes to the development of transport infrastructure that provides transportation of passengers and raw materials, finished products in the required volumes. 5. International transport highways pass through the region, which contributes to the development of the infrastructure of the surrounding areas. 6. Proximity to major centers of business cooperation and border cities. Railway transport in Ternopil region is widely used in both domestic and international relations. In 2020, its share in the structure of freight turnover was 22%, and passenger turnover - 2%. If we compare these data with the volume of traffic in 2016 (24% and 7%, respectively), we can conclude that the quarantine restrictions during the COVID-19 pandemic have a significant impact on the volume of rail transport.

Application of de-noising automatic coding method in freight volume prediction under intelligent logistics

Application of de-noising automatic coding method in freight volume prediction under intelligent logistics

Application of de-noising automatic coding method in freight volume prediction under intelligent logistics

Application of de-noising automatic coding method in freight volume prediction under intelligent logistics

Forecasting Brazilian Railway Freight Volume: An Unobserved Components Model Application

Forecasting Brazilian Railway Freight Volume: An Unobserved Components Model Application