Development Of A Railway Freight Demand Model For The Proposed Cape Fria To Katima Mulilo (Trans Caprivi Corridor) Railway Line

This research aimed at examining the freight flows along the Cape Fria to Katima Mulilo rail route on the Trans-Caprivi corridor(TCC)in Namibia and the causal relationship between freight shipment activities and related factors such as trade,GDP,travel time,travel cost and load capacity in order to develop a freight demand model to forecast future freight traffic.The objective of this paper was to aid in the achievement of the best allocation of freight demand to railway capacity and maximize the return on initial investments by investigating the unique variables which characterize freight traffic demand along the TCC,assessing identified variables which characterize freight traffic demand along the TCC in order to develop a freight demand model to assist the national railway operator to reliably predict future freight traffic along the TCC.In the first chapter a background was provided on the status of the railway freight transportation sector in the world and most importantly in Africa in order to provide context for the current railway freight situation in Namibia.A prelude was presented on Namibia highlighting key information on governance,population,economy and transportation ending with an in-depth overview of railway freight transportation in Namibia.In summary of the first chapter the scope for the research was presented after the background to highlight the limitations and delimitations of the study,thirdly the motivation for the study was outlined to cover the fundamental reasons for carrying out the study.Lastly specific objectives of the study,significance and content outline were canvassed to formulate the basis on which the remainder of the study paper stands.The second chapter focused on literature review of inter-regional freight demand describing in detail firstly the major inter-regional freight traffic demand influence factors of population,economic activity,load capacity,travel distance,price and time,industries,income,energy,environment and technology.Secondly the chapter covered most widely used inter-regional freight demand forecasting techniques categorizing them into qualitative and quantitative freight demand techniques.Thirdly a brief comparative analysis was conducted on the presented qualitative and quantitative freight demand techniques.In conclusion of the second chapter a detailed overview of inter-regional freight demand modeling was presented on the basis of the 4-step model with a detailed description of freight trip generation,freight trip distribution,freight trip mode choice and freight trip route assignment.Lastly,the second chapter provided a tabulation of literature summary.In chapter three,the methodology describes the procedure followed to adopt the freight demand model for forecasting the future freight demand on the TCC.An overview of the study area is provided with particular focus to the TCC and the far eastern region connecting to the corridor.Thereafter,a brief insight was presented into the study design and data collection approach spanning across various consulted data sources as well as previous studies conducted on the corridor.In conclusion model formulation is presented giving context to the approach used to identify the variables adopted within the model.In chapter four,the author firstly formulated initial four-step inter-regional freight demand forecasting model from the literature review which consists of freight trip generation,freight trip distribution,freight modal split,and freight traffic assignment.The study results in chapter four showed a 5.37%annual growth of foreign trade,1.21%annual growth in population and 11.86%annual growth in GDP per Capita between 2010 to 2017 along the TCC.On the other hand,the load capacity was measured at 686 400.00 tons/year/km depending on the capacity of the national railway operator Transnamib Holdings,while the travel time for a return trip was found to be 37 hours which is approximately 2 days.Travel cost was calculated at N$ 8 935 420.00/km emanating from the summation of 3 variables of,construction cost-N$ 8 863 000.00/km,maintenance cost-N$ 14 760/km and energy cost-N$ 57 660/km respectively.Freight traffic demand was computed for the base year 2020 in order to calibrate the model resulting in a forecast in foreign trade of 500 031.15 ton,population of 1 341 423,GDP per Capita of N$ 74 184.31 and total freight traffic of 1 736 791.10 ton-km for the year 2020.Lastly,from the preceding results the author developed the freight demand model for the TCC as,FTDMTCC=e1.11(TiTj)0.05(I)0.17(Cijm)0.13(tijm)0.33 which was used to establish freight traffic projections for the period of 2021 to 2030.A model validation was carried out using Microsoft Excel by comparing the correlation between the actual foreign trade and actual freight traffic for the years 2010 and 2017 with the forecasted foreign trade and freight traffic between 2021 and 2030 giving Pearson's product coefficients of r=0.12 and r=0.16 respectively,as well as r2=0.015 and r2=0.02 respectively which reasonably proves that since the r and r2 values are very similar there is strong correlation between the actual generated freight traffic and the forecasted freight traffic which is evident enough to conclude that the freight traffic model is valid.In conclusion,the study results showed a very gradual increase in freight shipment along the TCC which could be useful for operational profitability and long-term sustainability of the TCC railway.The study will contribute to having a more efficient and robust railway transportation system in Namibia capable of accommodating fast growing freight traffic demand.Moreover,given the increasing wave of environmental awareness and focus on issues such as global warming,the freight traffic demand projections in the study will provide a basis for further research work to establish for instance the effect of failure to shift the projected freight traffic from road to rail on air quality,environmental pollution and eventually human health which could attract more interest and research funding opportunities.21 figures,34 tables and 94 reference documents.