Development of a decision support tool for transit network design evaluation

Municipalities increasingly have less financial resources to spend on implementation of transport strategies and plans. This situation is putting pressure on transport professionals to minimize wasteful expenditure on projects that do not deliver high transport service improvements. As such, the need for efficient, pragmatic decision making on policy direction, infrastructure expenditure, or any transport interventions is becoming very critical. Thus, transport professionals are increasingly in need of tools to help them predict with increased accuracy the outcomes of their intended transport interventions. The City of Cape Town has a Bus Rapid Transport system called MyCiTi. Current MyCiTi operations are incurring losses. The service is kept running on the back of subsidies from the federal government. There is a need for rationalization of the system. However, with strained resources, the interventions on the system have to guarantee improvements. Overemphasis on the ability of MyCiTi BRT service to support transportation during the 2010 soccer world cup event heavily influenced the design of the network. As a result, network appraisal is one area that can be done on the system to identify areas of improvement. In this thesis, decision making support will be demonstrated using a network design appraisal process for the MyCiTi BRT system in Cape Town. The existing MyCiTi network will undergo network improvement using heuristic node insertion technique leading to multiple network scenarios in a modeling environment. Agent-Based demand mobility behavior simulation will be used on each of the network scenarios to come up with network performance indicators. These network performance indicators will be used in the multi-criteria decision analysis (MCDA) model to come up with a ranking of the network scenarios and help in deciding on the optimum network improvement intervention. Overall, findings of this research show the importance of weighting of the performance indicators. Where networks that score well in the performance indicator with the high weights also rank high. In conclusion, the study has demonstrated the importance of decision making support in interventions on complex systems like bus systems. Recommendations on the possible avenues of research stemming from this thesis have also been outlined

Full Issue 14(4)

il saggio esamina compiutamente la disciplina dell'art. 19 d.lgs. n. 5/200

Quantifying MyCiTi supply usage via Big Data and Agent Based Modelling

The MyCiTi is currently generating large volumes of raw transactional information in the form of commuter smartcard transactions, which can be considered Big Data. Agent Based modelling (ABM) has been applied internationally as a means of deriving actionable intelligence from Big Data. It is proposed that ABM can be used to unlock the hidden potential within the aforementioned data. This paper demonstrates how to go about developing and calibrating a MATSim-based ABM to analyse AFC data. It is found that data formatting algorithms are critical in the preparation of data for modelling activities. These algorithms are highly complex, requiring significant time investment prior to development. Furthermore, the development of appropriate ABM calibration parameters requires careful consideration in terms of appropriate data collection, simulation testing, and justification. This study serves as strong evidence to suggest that ABM is an appropriate analysis technique for MyCiTi data systems. Validation exercises reveal that ABM is able to calculate on board bus usage and system behaviour with a strong degree of accuracy (R-squared 0.85). It is however recommended that additional research be conducted into more detailed calibration activities, such as fine-tuning agent behaviour during simulation. Ultimately this research study achieves its explorative objectives of model development and testing, and paves a way forward for future research into the practical applications of Big Data and ABM in the South African context

The Multimodal Connectivity at Bus Rapid Transit (BRT) Stations and the Impact on Ridership

A multimodality index (MI) is developed to evaluate the accessibility and convenience of transit use by investigating the connectivity of a Bus Rapid Transit (BRT) with other modes of travel. Better connected stations increase transit system ridership, resulting in environmental and social equity gains. The integration of the Orange Line BRT system in Los Angeles with other travel modes, including bicycles, pedestrians, regular buses, and private automobiles, was analyzed using field observations and LA Metro data to create a multimodality index (MI). While multimodal connectivity of the Orange Line BRT system varies across stations, a positive relationship exists between ridership and the MI, indicating that the MI is a reliable predictor of transit ridership and a useful tool for transit planning

Modelling busway operation with mixed stopping and non-stopping buses

This thesis investigated the complexity of busway operation with stopping and non-stopping buses using field data and microscopic simulation modelling. The proposed approach made significant recommendations to transit authorities to achieve the most practicable system capacity for existing and new busways. The empirical equations developed in this research and newly introduced analysis methods will be ideal tools for transit planners to achieve optimal reliability of busways