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

This thesis is focused on microsimulation of city traffic, specifically a small city circuit in Brno. The thesis describes approaches for solving the problem of road network representation and presents basic methods and models needed for traffic simulation on the level of individual vehicles control as well as on the level of simulator control. In the case of more possible solutions to the given problem, the features and suitability of these solutions are compared. In the practical part of the thesis, the structure of the proposed simulator is presented with all the dependencies among individual submodels, along with the description of implementation details related to the individual parts.

Les travaux conduits dans le cadre de cette thèse ont pour but d’étendre le champ de validité des simulations de trafic en milieu urbain et péri-urbain, avec notamment une meilleure prise en compte du contexte de conduite, de l’hétérogénéité des véhicules (deux-roues motorisés, véhicule léger, poids lourd, etc.) et des comportements des conducteurs en termes d’occupation de l’espace au sol. Le but est de produire en simulation des comportements observés en situation réelle tels que les phénomènes de faufilement (deux-roues, véhicules d’urgence, cas des intersections). Nous abordons, la simulation du trafic routier en considérant une approche comportementale fondée sur les systèmes multi-agents. Des travaux précédents ont proposé des solutions non génériques, notamment pour le cas particulier des deux-roues motorisés. Nous proposons un nouveau modèle d’agent permettant de mieux prendre en compte le contexte de conduite et les comportements des conducteurs en termes d’occupation de l’espace. Nous dotons l’agent d’une représentation ego-centrée de l’environnement fondée sur le concept d’affordance. Nous utilisons ainsi les affordances pour identifier les actions possibles, en termes d’occupation de l’espace, offertes par l’environnement. Nous les utilisons en- suite pour construire une représentation ego-centrée de la situation. Le modèle d’agent proposé a été implémenté avec Archisim. Cette implémentation a permis de reproduire une situation de trafic réelle et de comparer les données simulées avec celles recueillies sur le terrain. Différentes expérimentations ont été menées afin d’évaluer la qualité de la solution proposée. / The work described in this thesis aims to improve the validity of traffic simulations in urban and suburban areas. We propose to consider the driving context, the heterogeneity of vehicles (motorized two-wheelers, vehicle, truck, etc.) and the driver behavior in terms of space occupation. The purpose is to produce in simulation the observed real world phenomena such as faufilement behavior (two-wheelers, emergency vehicles, cases of intersections). We address the traffic simulation byconsidering a behavioral approach based on multi-agent systems. Previous work have proposed non- generic solutions, for the particular case of motorized two-wheelers. We propose a new agent model to better take into account the context of driving and driver behavior in terms of space occupation. We endow agent driver with an ego-centered representation of the environment based on the concept of affordances. We use the affordances to identify the possible actions, in terms of space occupation, afforded by environment. The proposed agent model was implemented with ArchiSim. This implementation has allowed to reproduce a real traffic situation and to compare the results to real data. Different experiments were conducted to assess the quality of the proposed solution.

In order to improve the air quality in Uppsala, a proposition to introduce one of two new emission zones (EZ), starting in the year 2020, has been proposed. In what is called Environment Zone Class 2 (EZ2), only cars that meet emission class Euro 5 and higher are allowed and in Environment Zone Class 3 (EZ3), only electric, fuel cell and gas vehicles are allowed. The purpose of this thesis is to examine how EZ: s would affect the air quality, regarding nitrogen oxides (NOx) and particles (PMx), within the zone of the city of Uppsala. Using the traffic simulation software PTV Vissim and the emissions modeling software EnViver, four scenarios have been created, two representing today's fleet of vehicles and two examining a modified fleet. Scenario 1 examines an exclusion of all non EZ2 vehicles (Euro 4 and lower) within the zone and scenario 2 examines an EZ2 solely on the road Kungsgatan. Scenario 3 and 4 examine an EZ2 and EZ3 where all cars that do not currently meet the requirements for each EZ are replaced with ones that do. The results indicate that all proposals, except scenario 2, lead to a reduction of NOx and PM2 within the zone. Scenario 1 shows a decrease by 51% for NOx and 57% for PM10, scenario 3 shows a decrease by 17% and 24% respectively and scenario 4 shows a decrease by 66% and 43% respectively. For scenario 2 the emissions show an increase by 10% and 7% each within the zone.

Noise emissions from transportation remain one of the greatest environmental issues of modern day. Inhabitants in urban environments are especially exposed, with almost 80 million people in the European Union exposed to noise levels exceeding the recommended limits set by the World Health Organization (WHO). While the health-related effects from exposure of traffic noise are problematic and of utmost importance to reduce, availability to efficient transport is also an essential necessity. These conflicting requirements on transportation calls for a more holistic approach to traffic analysis, and  to understand the relation between these effects from the traffic. This work investigates properties of traffic, such as the exposure of noise emissions, the vehicle-specific energy demand and duration, to analyse the sustainability of transport. The traffic simulation software SUMO is used to provide a discrete traffic model with individual vehicles, combined with the European vehicle noise source model IMAGINE used to model discrete sound sources that allow for directivity in the sound field and is speed- as well as acceleration-dependent. The resulting cost related to the exposure of noise is then evaluated at several measurement points in the network using a willingness-to-pay (WTP) model. This allows for an analysis of the relation between noise exposure cost and energy efficiency through the estimation of the vehicle-specific energy demand. A time-varying traffic demand is added to analyse the effects of a varying traffic density and congestion to the relation between the different properties. Additionally, the concept of allocating the noise exposure cost down to individual vehicles by means of contributed acoustic energy is expanded to take the main contributing vehicles and time-segments into consideration, and to allow for a non-linear weighting factor. These allocation strategies also allow for a bias to assign a higher cost to noisier vehicles, as vehicles that contribute more to the overall noise exposure than others may be more easily identified. Lastly, the relation between the traffic properties are analysed by means of correlation. Initial studies indicate that the correlation is dependent on the traffic density and the amount of vehicle interaction. / Trafikbuller är en av de största miljöproblemen idag. Invånare i stadsmiljöer är särskilt utsatta, där nära 80 miljoner personer i Europeiska Unionen är utsatta för bullernivåer som överskrider Världshälsoorganisationens (WHO) angivna gränsvärden. Medan de hälso-relaterade effekterna från exponering av buller är på en ohållbar nivå och bör reduceras, så är även tillgänglighet till effektiv transport en nödvändighet. Dessa motstridiga krav på transportnätverket kräver en mer holistisk syn på trafikanalys, för att förstå relationen mellan dessa effekter från trafiken. Detta arbete undersöker de effekter som uppstår från trafiken, såsom bullerexponering, det fordons-specifika energibehovet och tiden i trafiken, för att analysera hållbarhetsaspekter för transporter. I detta arbete används trafiksimuleringsprogrammet SUMO för att erhålla en diskret trafikmodell med individuella fordon, i kombination med den europeiska fordonsbullermodellen IMAGINE som används för att modellera diskreta bullerkällor som tar hänsyn till direktivitet i ljudfältet samt fart- och accelerationsberoende. Den resulterande kostnaden för bullerexponeringen beräknas därefter för ett stort antal mätpunkter i nätverket genom en modell för betalningsvilja (WTP). Detta tillåter en analys av förhållandet mellan kostnad från bullerexponering och energieffektivitet baserat på det fordonsspecifika energibehovet. Ett tidsvarierande trafikflöde läggs på för att analysera effekterna från en varierande trafiktäthet och trängsel på förhållandet mellan de olika egenskaperna. Dessutom expanderas konceptet att allokera den buller-relaterade kostnaden ner till enskilda fordon baserat på deras enskilda bullerbidrag. Detta för att potentiellt kunna allokera en större del av den totala kostnaden till fordon som bidrar särskilt mycket till den totala bullernivån eller till särskilda tidsegment med höga bullernivåer, samt att tillåta en ickelinjär viktfunktion. Dessa allokeringsstrategier ger också möjligheten att allokera en högre kostnad till bullriga fordon, då fordon som bidrar mer till den totala bullernivån kan lättare identifieras. Slutligen analyseras förhållandet mellan trafikegenskaperna utifrån korrelation. Inledande studier visar att korrelationen beror på trafiktätheten och mängden fordonsinteraktion i trafiken.

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One of the most significant urban transport problems is traffic congestion. All major cities both in developed and developing countries are facing the problem due to increasing travel demand caused by increasing urbanization and the attendant economic and population growth. Recognizing the growing burden of traffic congestion, community leaders and transportation planners in Addis Ababa are still actively promoting large-scale road constructions to alleviate traffic congestion. Although Intelligent Transportation Systems(ITS) applications seem to have the potential to improve signalization performance, highly congested intersections in Addis Ababa are still controlled by a timed signal and manual operation. Moreover, these pre-timed signal controls are functioning sub-optimally as they are not being regularly monitored and updated to cope with varying traffic demands. Even though the benefits are well known theoretically, at the time of writing of this thesis, Adaptive Traffic Signal Controllers (ATSC) haven’t been deployed in Ethiopia and no research has been conducted to demonstrate and quantify their effectiveness. This master’s research thesis, therefore, intends to fill the identified gap, by undertaking a microscopic traffic simulation investigation, to evaluate the benefits of adopting a Traffic-responsive Urban Control (TUC) strategy and optimizing traffic signal timings. For the purpose of this study, an oversaturated three-intersection test corridor located in the heart of Addis Ababa city is modeled in VISSIM using real-world traffic data. After validating the calibrated model, the corridor was evaluated with the existing pre-timed, TRANSYT optimized pre-timed plan and TUC strategy. Multiple simulation runs were then made for each scenario alternatives and various measures of effectiveness were considered in the evaluation process. Simulation evaluation has demonstrated an average delay reduction of 24.17% when the existing pre-timed alternative is compared to TRANSYT optimized plan and 35% when compared to the TUC strategy. Overall evaluation results indicate that deploying the TUC strategy and optimizing the aging pre-timed signal plans exhibits a significant flow improvement. It is expected that the result of the thesis work will be an input for future comprehensive policy development processes.

Microscopic traffic simulation has become an important tool to investigate traffic efficiency and road safety. In order to produce meaningful results, incorporated driver behaviour models need to be carefully calibrated to represent real world conditions. In addition to macroscopic relationships such as the speed-density diagram, they should also adequately represent the average risk of accidents occurring on the road. In this thesis, I present a two stage computationally feasible multi-objective calibration process. The first stage performs a parameter sensitivity analysis to select only parameters with considerable effect on the respective objective functions to keep the computational complexity of the calibration at a manageable level. The second stage employs a multi-objective genetic algorithm that produces a front of Pareto optimal solutions with respect to the objective functions. Compared to traditional methods which focus on only one objective while sacrificing accuracy of the other, my method achieves a high degree of realism for both traffic flow and average risk. / Mikroskopisk trafiksimulering har blivit ett viktigt verktyg för att undersöka trafik effektivitet och trafiksäkerhet. För att producera meningsfulla resultat måste inbyggda drivrutinsbeteendemodeller noggrant kalibreras för att representera verkliga förhållanden i världen. Förutom makroskopiska relationer, såsom hastighetsdensitetsdiagrammet, bör de också på ett adekvat sätt representera den genomsnittliga risken för olyckor som uppträder på vägen. I denna avhandling presenterar jag en tvåstegs beräkningsberättigbar mångsidig kalibreringsprocess. Det första steget utför en parameterkänslighetsanalysför att bara välja parametrar med stor effekt på respektive objektiv funktioner för att hålla kalibrerings komplexiteten på en hanterbar nivå. Det andra steget använder en mångriktig genetisk algoritm som ger framsidan av Pareto optimala lösningar med hänsyn till objektivfunktionerna. Jämfört med traditionella metoder som fokuserar på endast ett mål, samtidigt som man offrar den andra, ger min metod en hög grad av realism för både trafikflöde och genomsnittlig risk.

Evaluating the challenges and opportunities of cooperative autonomous vehicles (CAV) require an adapted simulation methodology reproducing realistic driving and sensory contexts. In this paper, we propose a RounD-like CARLA scenario reproducing in CARLA the driving context recorded in the RounD dataset. We focus in particular on roundabout scenarios, as they are considered particularly challenging for CAV. We present the methodology followed to generate the CARLA scenario and describe challenges to reproduce trajectories corresponding to RounD. Origin and destination of vehicles, waypoint and speed are extracted from RounD for CARLA vehicles to closely reproduce the driving patterns observed in RounD. The benefit of such scenario are manyfold, such as evaluating control algorithms of CAVs, deep AI reinforcement learning, or vehicular sensor data sampling under realistic driving contexts. It notably will reduce the gap of AI mechanisms for CAV between simulation scenarios and realistic conditions.

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