Effects of feeder network operations on trunk-feeder network performance: a case study of Mitchells Plain, Cape Town
In South Africa, more than 65% of commuters use public transport every day. However, the public transport system which commonly takes the form of a trunk-feeder network is not structured to meet the needs of the different users. Taxis which are informal serve as feeders to an interchange while the trunk services depart the interchange in a scheduled formal manner. Because of this difference in the nature in which the two public transport services operate, it renders the intermodal system uncoordinated. It thus makes it difficult for transport planners to coordinate unscheduled feeder services to the scheduled trunk services. This study investigated how the feeder public transport service configurations and operations on trunk bus services can be integrated and coordinated. The research employed an agent-based simulation tool to model and simulate trunk-feeder operations and further investigate how the configuration and operational characteristics of the trunk-feeder public transport system impact the passenger travel performance. The modelled intermodal operations mimicked typical trunk-feeder operations as follows: passenger arrival at stops to wait for taxis; passengers boarding and alighting along the feeder route; transferring passengers alighting from taxis; and walking through the interchange to connect to their respective trunk services so as to reach their destinations. The output of the validated base simulation model i.e. system characteristics, configurations and parameters were utilized to determine the Key Performance Indicators (KPI) in the system. The analysis of the KPIs showed that there is indeed no co-ordination between feeder arrivals and trunk departures, and that this is mostly a result of inefficiencies in current operations in the feeder system. Scenarios were then developed to improve the trunk-feeder model where they focused on improving the efficiency of taxi feeder operations along the feeder route, as well as integrating and co-ordinating the feeder services to the trunk services. The results of the model analysis showed that integration of trunk and feeder services can be achieved through timed transfers; whereby taxi arrivals at the interchange are co-ordinated to bus departures from the interchange. This must of course be supplemented with other improvements tested in the scenarios on the feeder network. However, the operational behaviour of taxi feeder services is not predictable as a result of route non-compliance. This makes it difficult to plan timed transfers between them and formal bus and train services in order to achieve integration. It is therefore key that the transport authority and the taxi association's work closely to ensure that the regulations set about taxi operations and route compliance are followed. Without monitoring, the taxis will tend to operate in areas with high demand as operators are profit seeking as opposed to servicing the community and this will limit the success of this objective. Key words: Trunk-feeder, Taxi, simulation modelling, co-ordination, boarding & alighting, public transport integration, passengers
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