Abstract:
In South Africa, a number of BRT systems are currently either in the planning stage, detail
design and construction stage or operational. Cities such as Cape Town, Tshwane,
Johannesburg, Bloemfontein, Polokwane, Rustenburg, Nelson Mandela Bay and Durban are
currently in some BRT development or operational stage. These systems are being
implemented at much lower passenger demand than in the majority of developing nations
(Hensher & Golob, 2008), (City of Cape Town, 2012), (Rea Vaya, 2009), (Botha et. al., 2013).
Planning authorities in South Africa are required by the National Land Transport Act (NLTA) to
integrate all non-contracted services into a single public transport system (Republic of South
Africa, 2009). Current availability of funding through the Public Transport Infrastructure and
Systems grant (PTIS) and the Public Transport Operational Grant (PTOG), (Republic of South Africa, 2012), has made it possible for municipalities to plan, implement and operate such
systems.
No country possesses infinite funds to apply on the implementation and operation of public
transport systems. It is therefore important that an analysis should be done on bus based
infrastructure and operational alternatives. The incremental implementation of network wide
BRT like features, has however been proven to have greater benefit-cost ratios (Lindblom,
1979), rather than implementing a full BRT on a single line (Eddington, 2006), (Niles & Jerram,
2010), (Hitge & van Dijk, 2012) and (Hidalgo, c.a. 2006).
When the decision is made to implement a bus based public transport system, the planning
authority is faced with various questions. Two of the more critical questions faced are:
• What level of bus service should be implemented?
• What type of bus should be used?
The goal of this study therefore is, taking into consideration an incremental increase in
passenger demand, to find the optimum size of bus to use in combination with the extent of
public transport infrastructure to be implemented.
A model was created for this study in order to re-create a real life scheduled bus service for
each of the different variables. One of the variables used in this study is the type of bus, with a
single BRT bus, articulated bus and bi-articulated bus used in the model. Another variable used
in this study is the type of service, with a traditional bus service, operating in mixed traffic
(base case scenario), a London style bus lane service and a BRT service being used to populate
the model. Other variables include the level of traffic congestion experienced in the mixed lane
bus service and the passenger demand encountered on the public transport line.
Initially, the data obtained from the model shows, when compared to the same type of service,
a bi-articulated bus always has the best benefit-cost ratio. This is followed by an articulated
bus, with a single bus having the worst benefit-cost ratio. An increase in traffic only raises the
benefit-cost values, and does not alter the general trend of the services or buses.
