Transport modelling and travel forecasting are at the centre of attention of urban transportation planners. Demand models are used to determine the future projected traffic on the basis of determining the need for new infrastructure capacity to accommodate the future anticipated demand as well as to better understand people’s travel patterns for reasons of utilising strategic investment opportunities through land developments and implementation of policies.
The demand modelling follows the approach referred to as the four-stage transportation modelling, where travel simulations constructed on trip-based attempts to simulate choices made by travellers in given boundaries of a transportation system. The four-stage transport as shown in detail in Figure 1 includes simulation processes of trip generation, trip distribution, modal split and assignment described in more detail below.
Trip generation is used to define the magnitude of total daily travel in the model system, at the household and zonal level, for various trip purposes or activities. Each trip splits into a generation and attraction, where factors affecting the number of trips could be based on household characteristics, such as the number of people in the household as well as car availability and employment of the household members. Trip generation could be calculated by commonly adopted methods such as the collection of current demand by surveys, regression analysis, category analysis and trip information computer system.
After the number of demand of trips is found, trip distribution is the component of the analysis where through the use of a trip matrix, the trip maker’s origins and destinations can calculate the number of trips between one zone and another in an iterative manner.
Modal split is the most difficult part of the process. The trip distribution analysis yields a set of origin-destination tables created by analysing the zonal interchanges that tell us how many trips will be made. The modal split allows the modeller to analyse the mode of transport chosen by a person to make those trips.
Journeys between a given origin and destination depending on the journey purpose and mode availability in the area could heavily influence the mode choice such factors like the journey time and cost, comfort, safety and security, weather and more.
Modal integration such as park and ride, e-scooter and guided buses as well as policies made encourages vehicle drivers to switch to other modes of transport with the aim of improving the transport system of the area under study and promote the use of the transport system.
The assignment stage of the model is concerning the selection of routes between origins and destinations in transportation networks. Based on the analysis of the traveller’s mode choice in the previous step and the trip matrices created in trip distribution, helps to determine facility needs, costs and benefits as well as assign the number of trips to certain paths in the system called networks.
Various trips split into the highway, rail and others, are mostly dependent on cost since travellers usually select routes with the minimised travel cost for their journey. In this stage and with the use of computer power, assigned trip volume is compared to the capacity of the links and congestion of the system is analysed.