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This thesis deals with the impact of future traffic load on the level of traffic quality in Rokytova, Žarošická and Jedovnická streets after the opening of parts of the large urban ring road Tomkovo náměstí, Rokytova and Ostravská radiála. To assess these impacts, a microscopic traffic model is used, which is created in the Aimsun software using map data, directional survey at the affected intersections, traffic volumes and observed signal plans. The next part is the traffic engineering design of Žarošická and Jedovnická streets in several variants including their assessment.

The main goal of my diploma thesis is the design of transport-engineering measures on the Svatoplukova street with the focus on the finalization of the Great Brno ring road and the following changes of traffic intensity. For the implementation and simulation of my designed measures, I used the PTV Vissim modeling software. The simulation outputs were then evaluated and transformed into recommendations to be taken into consideration during the creation of future traffic-engineering measures in the given area.

Recent research at UCF into defining surrogate measures for identifying crash prone conditions on freeways has led to the introduction of several statistical models which can flag such conditions with a good degree of accuracy. Outputs from these models have the potential to be used as real-time safety measures on freeways. They may also act as the basis for the evaluation of several intervention strategies that might help in the mitigation of risk of crashes. Ramp Metering and Variable Speed Limits are two approaches which have the potential of becoming effective implementation strategies for improving the safety conditions on congested freeways. This research evaluates both these strategies in different configurations and attempts to quantify their effect on risk of crash on a 9-mile section of Interstate-4 in the Orlando metropolitan region. The section consists of 17 Loop Detector stations, 11 On-ramps and 10 off-ramps. PARAMICS micro-simulation is used as the tool for modeling the freeway section. The simulated network is calibrated and validated for 5 minute average flows and speeds using loop detector data. Feedback Ramp Metering algorithm, ALINEA, is used for controlling access from up to 7 on-ramps. Variable Speed Limits are implemented based on real-time speed conditions prevailing in the whole 9-mile section. Both these strategies are tested separately as well as collectively to determine the individual effects of all the parameters involved. The results have been used to formulate and recommend the best possible strategy for minimizing the risk of crashes on the corridor. The study concluded that Ramp Metering improves the conditions on the freeway in terms of safety by decreasing variance in speeds and decreasing average occupancy. A safety benefit index was developed for quantifying the reduction in crash risk and it indicated that an optimal implementation strategy might produce benefits of up to 55%. The condition on the freeway section improved with increase in the number of metered ramps. It was also observed that shorter signal cycles for metered ramps were more suitable for metering multiple ramps. Ramp Metering at multiple locations also decreased the segment wide travel-times by 5% and was even able to offset the delays incurred by drivers at the metered on-ramps. Variable Speed Limits (VSL) were individually not as effective as ramp metering but when implemented along with ramp metering, they were found to further improve the safety on the freeway section under consideration. By means of a detailed experimental design it was observed that the best strategy for introducing speed limit changes was to raise the speed limits downstream of the location of interest by 5 mph and not affecting the speed limits upstream. A coordinated strategy - involving simultaneous application of VSL and Ramp Metering - provided safety benefits of up to 56 % for the study section according to the safety benefit index. It also improved the average speeds on the network besides decreasing the overall network travel time by as much as 21%.

Recent research at the University of Central Florida addressing crashes on Interstate-4 in Orlando, Florida has led to the creation of new statistical models capable of calculating the crash risk on the freeway (Abdel-Aty et al., 2004; 2005, Pande and Abdel-Aty, 2006). These models yield the rear-end and lane-change crash risk along the freeway in real-time by using static information at various locations along the freeway as well as real-time traffic data that is obtained from the roadway. Because these models use the real-time traffic data, they are capable of calculating the respective crash risk values as the traffic flow changes along the freeway. The purpose of this study is to examine the potential of two Intelligent Transportation System strategies for reducing the crash risk along the freeway by changing the traffic flow parameters. The two ITS measures that are examined in this research are route diversion and ramp metering. Route diversion serves to change the traffic flow by keeping some vehicles from entering the freeway at one location and diverting them to another location where they may be more efficiently inserted into the freeway traffic stream. Ramp metering alters the traffic flow by delaying vehicles at the freeway on-ramps and only allowing a certain number of vehicles to enter at a time. The two strategies were tested by simulating a 36.25 mile section of the Interstate-4 network in the PARAMICS micro-simulation software. Various implementations of route diversion and ramp metering were then tested to determine not only the effects of each strategy but also how to best apply them to an urban freeway. Route diversion was found to decrease the overall rear-end and lane-change crash risk along the network at free-flow conditions to low levels of congestion. On average, the two crash risk measures were found to be reduced between the location where vehicles were diverted and the location where they were reinserted back into the network. However, a crash migration phenomenon was observed at higher levels of congestion as the crash risk would be greatly increased at the location where vehicles were reinserted back onto the network. Ramp metering in the downtown area was found to be beneficial during heavy congestion. Both coordinated and uncoordinated metering algorithms showed the potential to significantly decrease the crash risk at a network wide level. When the network is loaded with 100 percent of the vehicles the uncoordinated strategy performed the best at reducing the rear-end and lane-change crash risk values. The coordinated strategy was found to perform the best from a safety and operational perspective at moderate levels of congestion. Ramp metering also showed the potential for crash migration so care must be taken when implementing this strategy to ensure that drivers at certain locations are not put at unnecessary risk. When ramp metering is applied to the entire freeway network both the rear-end and lane-change crash risk is decreased further. ALINEA is found to be the best network-wide strategy at the 100 percent loading case while a combination of Zone and ALINEA provides the best safety results at the 90 percent loading case. It should also be noted that both route diversion and ramp metering were found to increase the overall network travel time. However, the best route diversion and ramp metering strategies were selected to ensure that the operational capabilities of the network were not sacrificed in order to increase the safety along the freeway. This was done by setting the maximum allowable travel time increase at 5% for any of the ITS strategies considered.

A transportation system designed to prioritize the mobility of automobiles cannot accommodate the growing number of road users. The Complete Streets policy plays a crucial part in transforming streets to accommodate multiple modes of transportation, especially active modes like biking and walking. Complete streets are referred to as streets designed for everyone and enable safety and mobility to all users. A strategy of complete streets transformation is to connect isolated complete street segments to form a complete network that improves active mobility and public transit ridership. This research assessed the impact of efficiently and equitably connecting and expanding the biking network using dedicated lanes on the safety and operation of the network in Atlanta, Georgia. These connections are aimed at increasing the multimodal use of the streets in midtown and downtown Atlanta and achieving the mobility and public health goals through the integration of various modes of travel. The evaluation was done by modeling a well-calibrated and validated network of Midtown and Downtown Atlanta in VISSIM using existing travel demand and traffic design conditions (i.e., the baseline or Scenario 0). A total of three different conditions: existing, proposed, and alternative conditions, were modeled to see the effectiveness of bike infrastructure design improvement and expansion. Three scenarios were then modeled as variations of modal demand of the different condition models. Scenarios modeled are based on input from the City and Community stakeholders. Using the trajectory data from microsimulation, the surrogate safety assessment model (SSAM) from FHWA was used to analyze the safety effect on the bike infrastructure improvement and expansion. Results of this study showed a positive impact of complete streets transformation on the streets of Midtown and Downtown Atlanta. These impacts are quantified in this thesis.

Over the past years, bicycles started to gain popularity and more people are now using it as amean of transportation. Nowadays, sustainability trends promote cycling as one of the greenestsolutions for the future in mobility. With this rising demand in the number of bicycle trips, there isa need to design adequate infrastructure fitted to the behavior of cyclists and their traffic patterns.Even though there is plenty information regarding car driving behavior, there is still a lack ofunderstanding in how cyclists behave. Consequently, the behavior of cyclists is often modelled byadjusting parameters from models originally designed for other types of users (e.g. car-followingmodels).The purpose of this degree project is to increase the understanding of the behavior of cyclists byinvestigating the extent to what car-following models can be used to simulate bicycle traffic andwhat effects relevant parameters have on the behavior of simulated cyclists and specific trafficcharacteristics. The main method is microscopic traffic simulation, through the simulation programVissim, of bicycle traffic flow on a two-way separated cycle path in Stockholm, withoutdisturbances from pedestrian and car traffic. In addition, a sensitivity analysis is presented, withthe support of the Elementary Effects method, of behavioral parameters of following, overtaking,lateral position, and the longitudinal gradient of the cycle path, and their effects on speed, lateralposition, and time headway.The sensitivity analysis showed that the minimum lateral distance between cyclists is a keyparameter to model following and overtaking behavior, while the gradient was found to be animportant factor that has a great impact on the bicycle traffic performance. Overall, the resultsindicated that the Vissim implementation of the Wiedemann car-following model is able toreproduce the speed and time headway on flat cycle paths with high flows, with goodapproximation to reality. However, the model failed to represent the effect of gradient, and thelateral position of cyclists could only be achieved with a low level of detail and accuracy.The understanding of the behavior of cyclists is crucial for the design and planning of infrastructurededicated to bicycles, so transport planners can consider the needs of cyclists. This projectcontributes to establish a baseline for bicycle traffic modelling and its adaptation of car-followingmodels to simulate cyclists and bicycle traffic. The awareness of these adaptations will help topromote cycling in order to achieve a more sustainable transport system

Traffic signal cycle lengths are traditionally optimized to minimize vehicle delay at intersections using the Webster formulation. This thesis includes two studies that develop new formulations to compute the optimum cycle length of isolated intersections, considering measures of effectiveness such as vehicle delay, fuel consumption and tailpipe emissions. Additionally, both studies validate the Webster model against simulated data. The microscopic simulation software, INTEGRATION, was used to simulate two-phase and four-phase isolated intersections over a range of cycle lengths, traffic demand levels, and signal timing lost times. Intersection delay, fuel consumption levels, and emissions of hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) were derived from the simulation software. The cycle lengths that minimized the various measures of effectiveness were then used to develop the proposed formulations. The first research effort entailed recalibrating the Webster model to the simulated data to develop a new delay, fuel consumption, and emissions formulation. However, an additional intercept was incorporated to the new formulations to enhance the Webster model. The second research effort entailed updating the proposed model against four study intersections. To account for the stochastic and random nature of traffic, the simulations were then run with twenty random seeds per scenario. Both efforts noted its estimated cycle lengths to minimize fuel consumption and emissions were longer than cycle lengths optimized for vehicle delay only. Secondly, the simulation results manifested an overestimation in optimum cycle lengths derived from the Webster model for high vehicle demands. / Master of Science

Cette thèse explore deux questions autour de la précarité énergétique en France. Quel(s) indicateur(s) adopter pour quantifier la précarité énergétique et capturer ses multiples dimensions? Dans quelle mesure la fiscalité écologique pourrait-elle amplifier le phénomène ou, au contraire, constituer une opportunité de le combattre?Un premier chapitre introduit les enjeux sociaux et économiques de la précarité énergétique en France, ainsi que les défis que ce phénomène soulève pour les acteurs publics dans le cadre de la transition écologique (chapitre 1). Puis la thèse s'organise en deux grandes parties. La première partie concerne la quantification de la précarité énergétique. Je commence par rappeler les débats actuels autour de la mesure de la précarité énergétique et par souligner les limites des approches existantes (chapitre 2). Puis, j’explore la dimension transport du phénomène et propose un indice composite qui cible les différents facteurs qui contraignent la mobilité des ménages et leurs possibilités d’adaptation. Cet indice identifie trois niveaux d’exposition à une hausse des prix des carburants : précarité, vulnérabilité et dépendance (chapitre 3). Je poursuis ensuite la réflexion sur la construction d’un indice multidimensionnel de précarité énergétique et je cherche à mettre à jour ses implications politiques. Deux indices sont élaborés : un pour le logement et un pour le transport. Je montre comment ces nouveaux indices, parce qu’ils s’intéressent au cumul des facteurs qui désavantagent les ménages en matière d’énergie, permettent de limiter les erreurs d’inclusion et d’exclusion reprochées aux approches classiques. Une application dans le contexte français apporte de nouvelles perspectives sur le ciblage des réponses politiques et souligne la nécessité de remédier aux dimensions non monétaires de la précarité énergétique (chapitre 4).La seconde partie concerne les impacts distributifs de la fiscalité carbone. A partir d'une revue de la littérature, je précise les enjeux méthodologiques et les choix de modélisation pour rendre compte de manière satisfaisante de la distribution des impacts (chapitre 5). Je développe ensuite un modèle de microsimulation spécialement conçu pour évaluer l’impact sur les ménages de la taxe carbone française. Ce modèle simule, pour un échantillon représentatif de la population française, les taxes prélevées sur leur consommation d’énergie dans le logement et le transport. Je l’utilise pour quantifier l’impact de la taxe carbone sur les inégalités et la précarité énergétique. Enfin, j’explore ensuite différents scénarios de redistribution aux ménages avec pour objectif de corriger les iniquités engendrées - en particulier compenser la régressivité de la taxe carbone et combattre la précarité énergétique. J’évalue le coût de ces mesures au regard des recettes de la taxe carbone (chapitre 6). / This thesis explores two questions about fuel poverty in France: What indicator(s) should be adopted to quantify fuel poverty and capture its multiple dimensions? To what extent does ecological taxation amplify the phenomenon or, on the contrary, provides an opportunity to fight it?A first chapter introduces the social and economic issues of fuel poverty in France, as well as the challenges this phenomenon raises for public actors in the context of an ecological transition (chapter 1). Then the thesis is divided into two main parts.The first part deals with the measurement of fuel poverty. I start by highlighting the current debates on the measurement of fuel poverty and the limitations of existing approaches (chapter 2). Next, I explore the transport dimension of fuel poverty and I propose a composite index of the various factors that constrain household mobility and their possibilities to adapt to higher fuel prices. This index identifies three levels of exposure to rising fuel prices: precariousness, vulnerability and dependence (chapter 3). I then continue studying the design of a multidimensional index of energy poverty and I seek to uncover its political implications. Two indices are developed: one for housing and one for transport. I show how these new indices, through addressing the cumulative factors that disadvantage households in terms of energy, can help limit the inclusion and exclusion errorsfrom which conventional approaches suffer. Quantification in the French context brings new insights on the targeting of policy responses and emphasizes the need to address the non-monetary dimensions of fuel poverty (chapter 4). The second part studies the distributive impacts of carbon taxation. Based on a review of literature, I discuss the methodological issues and the modelling choices to represent the distribution of impacts (chapter 5). I then develop a microsimulation model to assess the impact of the French carbon tax on households. This model simulates, for a representative sample of the French population, the taxes levied on their energy consumption in housing and transport. I use this model to quantify the impact of the carbon tax on inequality and fuel poverty. Finally, I explore different scenarios of redistribution of carbon tax revenues to households, with the objective to correct the found inequities - in particular, to compensate for the regressivity of the carbon tax and to reduce fuel poverty. I evaluate the cost of these measures in respect to the amount of carbon tax revenues (chapter 6).

Cette thèse traite deux sujets distincts, les deux représentant des enjeux importants pour un grand nombre de Pays d’Europe Centrale et Orientale (PECO). La première partie porte sur les emprunts en devises étrangères. Plusieurs études antérieures montrent que dans de nombreux PECO, l’endettement en devises étrangères a augmenté de manière considérable avant la crise et est devenu un enjeu majeur pour les entreprises, les ménages et pour la politique budgétaire et monétaire. Pour évaluer les risques associés à l’endettement excessif en devises étrangères, nous étudions la volonté des entreprises d’apparier la composition en devises de leurs actifs et leurs passifs ainsi que leurs incitations à dévier de l’appariement parfait. Nos résultats fournissent des preuves solides à l’appui du rôle de la couverture naturelle. Néanmoins, ce dernier n’est pas le motif principal d’endettement en devise étrangères : le motif de couverture naturelle n’explique qu’environ 10 à 20 pour cent de la dette totale en devises étrangères des entreprises avant et pendant la crise, respectivement. La plus grande partie de la dette en devises étrangères correspondrait, au moins en Hongrie, à des positions de carry trade détenues par des sociétés non financières. La deuxième partie de la thèse est consacrée à l’exploration des liens entre les systèmes socio-fiscaux et l’offre de travail à la marge extensive. Le deuxième chapitre propose une nouvelle stratégie de modélisation de l’offre de travail comme alternative aux deux approches dominantes basées sur le calcul marginal et les modèles d’utilité aléatoire. Finalement, le dernier chapitre utilise ce modèle pour quantifier la part de la différence entre les taux d’activité tchèque et hongrois qui peut être expliquée par les divergences des systèmes d’imposition et de protection sociale. Les estimations donnent des élasticités d’offre de travail similaires, ce qui suggère que les préférences individuelles sont essentiellement identiques dans les deux pays. Nos résultats montrent que la moitié de l’écart entre les taux d’activité s’explique par les différences des systèmes socio-fiscaux. / This thesis deals with two distinct topics, both of them representing central issues for many Central and Eastern European (CEE) countries. The first part of the thesis focuses on foreign currency (FX) lending. Several previous studies point out that in many CEE countries, FX borrowing rose significantly before the crisis and has become a major challenge for firms, households and for fiscal and monetary policy. To evaluate the risks associated with excessive FX indebtedness, we investigate firms’ willingness to match the currency composition of their assets and liabilities and their incentives to deviate from perfect matching. Our results provide strong evidence to support the role of natural hedging, however, it is not the primary motivation for firms to choose foreign currency : it explains only about 10 percent of the overall corporate FX debt during the pre-crisis and 20 percent during the post-crisis periods. Most likely, the largest part of the corporate FX debt, at least in Hungary, corresponds to open carry trade positions held by non-financial corporations. The second part of the thesis is devoted to exploring the links between tax-benefit systems and labour supply at the extensive margin. The second chapter presents an alternative modelling strategy of labour supply to the two dominating approaches based on marginal calculus and on random utility models. Finally, the last chapter uses this model to quantify the difference between the Hungarian and the Czech participation rates that can be attributed to differences in taxation and welfare benefits. We find that the estimated labour supply elasticities for the Czech Republic are very close to the results for Hungary, suggesting that, at least in this dimension, individual preferences are similar in the two countries. Results suggests that about one-half of the total difference in the participation rates can be explained by differences in the tax-benefit systems.