The Method of Selecting the Key Freight Transport Industries Based on Weaver-Thomas Index

Regional freight transportation demand is an important basis for transportation planning. Because of the large number of industries, the survey of related industries for regional freight transportation demand is workload and complicated. Therefore, we can grasp the formation and distribution of regional freight transportation demand by analyzing the industries that can generate larger number of transportation demand.

The importance of disaggregated freight flow forecasts to inform transport infrastructure investments

This article presents the results of a comprehensive disaggregated commodity flow model for South Africa. The wealth of data available enables a segmented analysis of future freight transportation demand in order to assist with the prioritisation of transportation investments, the development of transport policy and the growth of the logistics service provider industry. In 2011, economic demand for commodities in South Africa’s competitive surface-freight transport market amounted to 622 million tons and is predicted to increase to 1834m tons by 2041, which is a compound annual growth rate of 3.67%. Fifty percent of corridor freight constitutes break bulk; intermodal solutions are therefore critical in South Africa. Scenario analysis indicates that 80%of corridor break-bulk tons can by serviced by four intermodal facilities – in Gauteng, Durban, Cape Town and Port Elizabeth. This would allow for the development of an investment planning hierarchy, enable industry targeting (through commodity visibility), ensure capacity development ahead of demand and lower the cost of logistics in South Africa.

Distributed Data Management of Daily Car Pooling Problems

The increased human mobility, combined with high use of private cars, increases the load on the environment and raises issues about the quality of life. The use of private cars lends to high levels of air pollution in cities, parking problems, noise pollution, congestion, and the resulting low transfer velocity (and, thus, inefficiency in the use of public resources). Public transportation service is often incapable of effectively servicing non-urban areas, where cost-effective transportation systems cannot be set up. Based on investigations during the last years, problems related to traffic have been among those most commonly mentioned as distressing, while public transportation systems inherently are incapable of facing the different transportation needs arising in modern societies. A solution to the problem of the increased passenger and freight transportation demand could be obtained by increasing both the efficiency and the quality of public transportation systems, and by the development of systems that could provide alternative solutions in terms of flexibility and costs between the public and private ones. This is the rationale behind so-called Innovative Transport Systems (ITS) (Colorni et al., 1999), like car pooling, car sharing, dial-a-ride, park-and-ride, card car, park pricing, and road pricing, which are characterized by the exploitation of innovative organizational elements and by a large flexibility in their management (e.g., traffic restrictions and fares can vary according with the time of day).

Freight Planning Typology

A layered architecture for freight transportation demand modeling entails the construction of a statewide freight transportation demand model by separately simulating traffic for one commodity at a time. Layers can then be added together to construct a comprehensive model that includes the most significant freight flows. Most state or regional economies are dominated by a few economic sectors, and models can be constructed for those sectors that generate the most freight traffic and/or are the most important to the regional economy. Freight traffic demand modeling in intercity applications is more likely to focus on economic development, local infrastructure improvements, maintenance, and similar policy and planning concerns than on system capacity issues. Thus, it is more important to understand changes in traffic growth by economic sector than as the composite of all freight traffic. This method is less data intensive and more easily understood by transportation professionals than previous approaches. The layered approach is therefore more likely to achieve the desired objectives than would general models, which attempt to forecast heterogeneous freight transportation demands simultaneously. This approach is demonstrated through a case study using the meat products and farm machinery industries in Iowa. Other commodities will be added in the future to complete a model of Iowa’s statewide freight transportation demand. A framework is presented for organizing and identifying planning goals, key issues, and predominant commodities for intercity freight transportation. Although examples are provided, specific recommendations addressing the full range of issues, data collection activities, tools, and urban applications are suggested for further study. A case study demonstrates the approach used for one issue, one mode, and two commodities, which could be repeated elsewhere for similar applications.

Forecasting Short-Term Freight Transportation Demand: Poisson STARMA Model

A framework for analyzing, describing, and forecasting freight flows for operational and tactical purposes is presented. A dynamic econometric model is proposed. This model incorporates the spatial and temporal characteristics of freight demand within a stochastic framework. The model was applied in an actual context and its performance was compared with standard time series models (benchmark) for forecasting ability. The proposed model outperformed the benchmark from the econometric viewpoint. Extensive diagnostic checking and sensitivity analysis confirmed the robustness of the modeling methodology for short-term forecasting applications.