The doctoral dissertation investigates the consequences of multimodal traveling for designing multimodal transport networks. It describes the characteristics of multimodal travel today and assesses its future potential. The analysis focuses on the way transport transport networks are organized in hierarchical network structures and determines the main mechanisms leading to these hierarchical network structures

The use and management of multimodal transport systems, including car-pooling and goods transportation, have become extremely complex, due to their large size (sometimes several thousand variables), the nature of their dynamic relationships as well as the many constraints to which they are subjected. The managers of these systems must ensure that the system works as efficiently as possible by managing the various causes of malfunction of the transport system (vehicle breakdowns, road obstructions, accidents, etc.). The detection and resolution of conflicts, which are particularly complex and must be dealt with in real time, are currently processed manually by operators. However, the experience and abilities of these operators are no longer sufficient when faced with the complexity of the problems to be solved. It is thus necessary to provide them with an interactive tool to help with the management of disturbances, enabling them to identify the different disturbances, to characterize and prioritize these disturbances, to process them by taking into account their specifics and to evaluate the impact of the decisions in real time. Each chapter of this book can be broken down into an approach for solving a transport problem in 3 stages, i.e. modeling the problem, creating optimization algorithms and validating the solutions. The management of a transport system calls for knowledge of a variety of theories (problem modeling tools, multi-objective problem classification, optimization algorithms, etc.). The different constraints increase its complexity drastically and thus require a model that represents as far as possible all the components of a problem in order to better identify it and propose corresponding solutions. These solutions are then evaluated according to the criteria of the transport providers as well as those of the city transport authorities. This book consists of a state of the art on innovative transport systems as well as the possibility of coordinating with the current public transport system and the authors clearly illustrate this coordination within the framework of an intelligent transport system. Contents 1. Dynamic Car-pooling, Slim Hammadi and Nawel Zangar. 2. Simulation of Urban Transport Systems, Christian Tahon, Thérèse Bonte and Alain Gibaud. 3. Real-time Fleet Management: Typology and Methods, Frédéric Semet and Gilles Goncalves. 4. Solving the Problem of Dynamic Routes by Particle Swarm, Mostefa Redouane Khouahjia, Laetitia Jourdan and El Ghazali Talbi. 5. Optimization of Traffic at a Railway Junction: Scheduling Approaches Based on Timed Petri Nets, Thomas Bourdeaud’huy and Benoît Trouillet. About the Authors Slim Hammadi is Full Professor at the Ecole Centrale de Lille in France, and Director of the LAGIS Team on Optimization of Logistic systems. He is an IEEE Senior Member and specializes in distributed optimization, multi-agent systems, supply chain management and metaheuristics. Mekki Ksouri is Professor and Head of the Systems Analysis, Conception and Control Laboratory at Tunis El Manar University, National Engineering School of Tunis (ENIT) in Tunisia. He is an IEEE Senior Member and specializes in control systems, nonlinear systems, adaptive control and optimization. The multimodal transport network customers need to be oriented during their travels. A multimodal information system (MIS) can provide customers with a travel support tool, allowing them to express their demands and providing them with the appropriate responses in order to improve their travel conditions. This book develops methodologies in order to realize a MIS tool capable of ensuring the availability of permanent multimodal information for customers before and while traveling, considering passengers mobility.

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.

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.

In New Mobilities: Smart Planning for Emerging Transportation Technologies, transportation expert Todd Litman examines 12 emerging transportation modes and services that are likely to significantly affect our lives: bike- and carsharing, micro-mobilities, ridehailing and micro-transit, public transit innovations, telework, autonomous and electric vehicles, air taxis, mobility prioritization, and logistics management. Public policies around New Mobilities can either help create heaven, a well-planned transportation system that uses new technologies intelligently, or hell, a poorly planned transportation system that is overwhelmed by conflicting and costly, unhealthy, and inequitable modes. His expert analysis will help planners, local policymakers, and concerned citizens to make informed choices about the New Mobility revolution.

Transport Nodal System provides a comprehensive introduction to the development of transport nodes and nodal systems, focusing on economic, operational, management, planning, policy, regulation and sustainability perspectives. Through a deep analysis on different types of transport nodes from diverse perspectives, this book shows the major issues and challenges that transport node planners, managers, and policymakers face, and how to address them. The book provides a clear framework for identifying the common attributes across all nodes that contribute to the efficient operations, planning, and management of transport facilities. Transport nodes such as seaports, inland terminals, airports, highways, and railroads are hubs in a multimodal transportation network that facilitate the smooth operation of passengers and freight. The book uniquely uses the transport node itself rather than a specific type of structure for a specific type of transport mode as the primary focus of analysis. While stressing the importance of transport nodes in developing efficient logistics and supply chains, the book also demonstrates that transport nodes are geographically embedded within a particular location, and that operations are inevitably affected by local factors, such as culture, the economy, the political and regulatory environment and other institutions. Provides a unified look at multimodal transportation nodes to gain a better understanding of total system performance Includes numerous case studies from developed and emerging economies Uses an interdisciplinary approach where policy, regulations, economics, strategic management, operations, sustainability and technological innovation are considered together Features chapters by scholars who specialize in different transport modes (land, sea and air) Up-to-date outcomes utilizing author’s original research provide a systematic investigation of the nodal system in both theory and practice