The public transport system in South Africa is in a precarious state, capturing no more than 50% of the passenger market. The three public transport modes that are currently utilized train, bus, and minibus-taxi are competing for market share instead of complementing one another. Furthermore, most public transport networks have not been properly redesigned over the past three decades. Improvements were initiated reactively in the past: transit stops and routes were added or removed from the network when demand fluctuated. This reactive process has diminished the confidence of commuters in the public transport networks, forcing commuters to use private transport. A proactive redesign method is needed one that includes all the modes of public transport, and anticipates an increase in demand and rapid development in geographic areas, while ensuring good accessibility to the network. Current network design models do not include multiple modes of public transport, and are based on the geographical layout of developed cities and their particularities, which makes them unsuitable for the South African environment with its unique land use disparities. This dissertation proposes a multimodal network design model that is capable of designing real world and large scale networks for the South African metropolitan areas. The City of Tshwane Metropolitan Municipality (CTMM) transport network area was used to develop and test the model, which consists of four components. The Geographic Information System (GIS) component has a central role in storing, manipulating, and exchanging the geographic data within the model. For the GIS the appropriate input data is identified, and a design for the geo-database is proposed. The Population Generation Algorithm (PGA) component translates the demographic data into point data representing the transit demand in the study area. The Bus Stop Placement Algorithm (BSPA) component is a metaheuristic that searches for near-optimal solutions for the placement of bus stops in the study area. A novel solution approach proposed in this dissertation uses geographic data of commuters to evaluate the bus stop placement in the study area. The Multimodal Network Design Algorithm (MNDA) component also employs a metaheuristic, enabling the design of near-optimal multimodal networks. The addition of multiple modes to the Transit Network Design Problem (TNDP) is also a novel and significant contribution. The two metaheuristic components are first tested on a test network, and subjected to a comprehensive sensitivity analysis. After identifying suitable parameter values and algorithm settings, the components are applied to the entire CTMM.

The 4 volume set LNCS 12112-12114 constitutes the papers of the 25th International Conference on Database Systems for Advanced Applications which will be held online in September 2020. The 119 full papers presented together with 19 short papers plus 15 demo papers and 4 industrial papers in this volume were carefully reviewed and selected from a total of 487 submissions. The conference program presents the state-of-the-art R&D activities in database systems and their applications. It provides a forum for technical presentations and discussions among database researchers, developers and users from academia, business and industry.

What determines how cities move on? The ever-increasing challenges to urban mobility come in many forms, and approaches to address them range from the technically ingenious to attempts to change travel behaviour. Key amongst factors essential to the success of any such approach is whether the urban environment proves to be fertile ground for the desired progress. Another vital determinant of success is how well individual measures to engineer the transport system interact with other developments. This leads to the principal subject of Megacity Mobility Culture: the basic principles that determine the paths along which cities move. This book demonstrates that the concept of ‘mobility culture’ provides a framework for understanding the development of urban transport which transcends the boundaries between academic disciplines. Based on a discussion of the diversity of megacities worldwide, it provides help in navigating the complexity of megacity mobility culture. Experts from megacities around the world each take the reader on a journey to their own city and its mobility culture, giving a deeper insight into the unique evolutionary paths of mobility that these places have taken, and what lies before them. Whilst acknowledging the overwhelming diversity of cities worldwide, the authors also identify common denominators behind the evolution of urban transport systems – seven temperaments which are found in a unique mix in any given city, defining the character of its mobility culture. The Institute for Mobility Research is a research facility of the BMW Group. It deals with future developments and challenges relating to mobility across all modes of transport, with automobility being only one aspect among many. Taking on an international perspective, ifmo’s activities focus on social science and sociopolitical, economic and ecological issues, but also extend to cultural questions related to the key challenges facing the future of mobility. The work of the Institute is supported by an interdisciplinary board of renowned scientists and scholars, and by representatives of BMW, Deutsche Bahn, Lufthansa, MAN, Siemens and The World Bank.

The growing mobility needs of travellers have led to the development of increasingly complex and integrated multi-modal transit networks. Hence, transport agencies and transit operators are now more urgently required to assist in the challenging task of effectively and efficiently planning, managing, and governing transit networks. A pre-condition for the development of an effective intelligent multi-modal transit system is the integration of information and communication technology (ICT) tools that will support the needs of transit operators and travellers. To achieve this, reliable real-time simulation and short-term forecasting of passenger demand and service network conditions are required to provide both real-time traveller information and successfully synchronise transit service planning and operations control. Modelling Intelligent Multi-Modal Transit Systems introduces the current trends in this newly emerging area. Recent developments in information technology and telematics have enabled a large amount of data to become available, thus further attracting transport researchers to set up new models outside the context of the traditional data-driven approach. The alternative demand-supply interaction or network assignment modelling approach has improved greatly in recent years and has a crucial role to play in this new context.

This book develops models, results and algorithms for optimizing public transportation from a customer-oriented viewpoint. The methods used are based on graph-theoretic approaches and integer programming. The specific topics are all motivated by real-world examples which occurred in practical projects: location of stops, management of delay, and tariff zone design. An appendix summarizes some of the basics of optimization needed to interpret the material in the book.