Public transit is becoming an increasing important field of study to combat global issues such as traffic congestion and climate change. Accurate simulation of public transit is therefore likewise vital, as it is an important tool for understanding potential impacts of public transit policies. The research presented in this thesis describes the implementation of a multimodal, dynamic, agent-based supply-side simulation model of public transit implemented in the open-source platform MATSim for the city of Toronto. Transit schedule data was converted from Google Transit Feed Specification (GTFS) and map-matched to a region-wide road network to obtain a congestion-based multimodal assignment for transit. Volume-based results from the assignment showed under-prediction of subway volumes and slight over-prediction of bus volumes, but were generally comparable with static EMME/3 assignment for the same data. Travel time analysis indicated that further calibration of network specification is needed.

Transport demand planning in South Africa is a neglected field of study, using obsolete methods to model an extremely complex, dynamic system composed of an eclectic mix of First and Third World transport technologies, infrastructure and economic participants. We identify agent-based simulation as a viable modelling paradigm capable of capturing the effects emerging from the complex interactions within the South African transport system, and proceed to implement the Multi-Agent Transport Simulation Toolkit (MATSim) for South Africa's economically important Gauteng province. This report describes the procedure followed to transform household travel survey, census and Geographic Information System (GIS) data into an activity-based transport demand description, executed on network graphs derived from GIS shape files. We investigate the influence of network resolution on solution quality and simulation time, by preparing a full network representation and a small version, containing no street-level links. Then we compare the accuracy of our data-derived transport demand with a lower bound solution. Finally the simulation is tested for repeatability and convergence. Comparisons of simulated versus actual traffic counts on important road network links during the morning and afternoon rush hour peaks show a minimum mean relative error of less than 40%. Using the same metric, the small network differs from the full representation by a maximum of 2% during the morning peak hour, but the full network requires three times as much memory to execute, and takes 5.2 times longer to perform a single iteration. Our census- and travel survey-derived demand performs significantly better than uniformly distributed random pairings of home- and work locations, which we took to be analogous to a lower bound solution. The smallest difference in corresponding mean relative error between the two cases comes to more than 50%. We introduce a new counts ratio error metric that removes the bias present in traditional counts comparison error metrics. The new metric shows that the spread (standard deviation) of counts comparison values for the random demand is twice to three times as large as that of our reference case. The simulation proves highly repeatable for different seed values of the pseudo-random number generator. An extended simulation run reveals that full systematic relaxation requires 400 iterations. Departure time histograms show how agents 'learn' to gradually load the network while still complying with activity constraints. The initial implementation has already sparked further research. Current priorities are improving activity assignment, incorporating commercial traffic and public transport, and the development and implementation of the minibus taxi para-transit mode. Copyright / Dissertation (MEng)--University of Pretoria, 2009. / Industrial and Systems Engineering / unrestricted

L’Analyse du Cycle de Vie (ACV) est une méthode d’évaluation multicritère des impacts environnementaux des biens et services. A ces débuts, l’ACV, dite Attributionnelle (ACVA), s’est attachée à analyser les impacts environnementaux dans des situations statiques pour la réalisation d’études comparatives, la communication environnementale et le développement de produits. De récents développements méthodologiques ont vu l’émergence de l’ACV Conséquentielle (ACVC) qui vise à quantifier les impacts directs et indirects de changements, via les mécanismes de marchés, permettant ainsi l’évaluation de politiques publiques. Cette thèse vise à proposer un cadre méthodologique pour l’évaluation d’instruments de politiques publiques dans le secteur de l’élevage laitier en combinant ACV et modèles économiquesElle s’articule autour de trois axes : i) identification et caractérisation des performances environnementale de technologies de production laitières par ACVA ; ii) adaptation du modèle économique MATSIM-LUCA pour les besoins de la thèse ; iii) évaluation par ACVC des impacts environnementaux de la suppression des quotas laitiers et de l’introduction d’une prime à l’herbe en Europe. Les travaux réalisés fournissent : i) une première proposition méthodologique pour l’évaluation d’instruments de politiques publiques par ACVC dans le secteur de l’élevage et ii) plusieurs pistes d’amélioration nécessaires pour rendre la méthode opérationnelle pour les décideurs publics. / Life Cycle Assessment (LCA) is a multicriteria method to assess environmental impacts of goods and services. In its early stages, LCA, known as Attributional (ALCA), was used to assess environmental impacts in a status-quo situation for benchmarking, environmental communication and product development. Recent methodological developments led to Consequential LCA (CLCA), which aims to quantify direct and indirect impacts of changes, through market mechanisms, allowing for public policy assessment. The aim of this Ph.D. thesis is to develop a methodological framework to assess public policy instruments in the livestock sector by combining LCA and economic modellingThis thesis is organized into three axes: i) identification and characterization of environmental performances of dairy production technologies through ALCA; ii) adaptation of MATSIM-LUCA economic model to the needs of the thesis; iii) environmental impact assessment through CLCA of dairy quota removal and implementation of a grass premium in the European Union. This work provides i) initial development of a methodological framework for assessing public policy instruments in the livestock sector and ii) identification of several improvements needed to make the method operational for stakeholders.