Growth Modelling of the Transportation System in Nigeria for the Purposes of Supporting Strategic Planning
Joshua O Adegoke, Birmingham City University, Manji Srai, Birmingham City University, Adrian C. Cole,
The study proposes an alternative approach to data estimation using modelling and simulation techniques using heuristic and deterministic approaches.
Nigeria (and other developing nations) will need to make a contribution towards reducing dependence on the use of fossil fuels within the transport (and other) sectors as part of the global CO2 reduction initiative. The use of the modelling environment is a much-needed tool to kick-start such initiatives. However, the quality of such a model is widely dependent on the availability and quality of the data it uses. Data quality represents a challenge for developing nations. The official transport data in Nigeria has been proven to be unreliable producing implausible and unsustainable predictions.
Therefore, the study proposes an alternative approach to data estimation using modelling and simulation techniques using heuristic and deterministic approaches. The data transformation (modelling) of the most reliable transport data source on Nigeria is explored with some known theoretical probability functions through the method of curve fitting for model selection. The best-fit model out of the four explored was found to be the ‘physical model’ which is used to represent the best estimate of vehicle growth in the country by 2050 at an approximately constant fuel supply. The country has an abundance of natural gas with almost zero use in the transport sector to transit into a low-carbon economy. One way the study considers a solution is through the introduction of natural gas as a transport fuelling option. The method adopted is a superimposition of the physical model on Lotka-Volterra equations in a prey-predator environment. The simulation supports the creation of various scenarios that represent the dynamic interaction between Conventional Vehicles (CV) as prey and Natural Gas Vehicles (NGV) as a predator with induced fuel change in the vehicle fleet. The scenarios considered are: non-intervention, moderate intervention and extreme intervention with different shares of 100% CV domination, 75% CV & 25% NGV and 20% CV & 80% NGV respectively in the country’s vehicle fleet. The results highlight how the fuel change dynamics influence the emergence of the total number of each vehicle type.
Keywords: Growth-Modelling. Curve-fitting. Fuel-switching.
Association for European Transport