The goal of the research is to devise an equitable road pricing system which would leave the majority of routes free of tolls, so that low income people would suffer no cash loss although they would probably suffer loss of time. The aims of the dissertation are twofold. The first is to provide a numerical analysis of how urban commuters with differing abilities to pay would respond to additional road user charges. The welfare implications of such differential responses are examined and their policy implications analysed. The second aim is to develop a practical framework to model congestion pricing policies in the context of heterogeneous users. To achieve these aims, the following objectives have been set: (a) Using a simple network with two parallel competing routes, determine both welfare maximising and revenue maximising tolls under the constraint that only one route can be priced. In this setting, determine the allocation of traffic between the alternative routes, the efficiency gain, the revenue, the changes in travel cost and the distributional effects. (b) Establish a realistic model of an actual urban area to examine the impacts of selectively tolling congestible routes. As in the simple network case, assess the effects of toll policy on traffic distribution, network efficiency, revenues, and the welfare of the individual consumer and society. (c) Evaluate whether the non-identical treatment of users will enhance the acceptability of congestion pricing as a transport policy. Results from the simulations indicate that non-identical treatment of drivers? responses to toll charges provides better understanding of the differential impacts of various pricing policies. Allowing for heterogeneity in time valuation provides a better assessment of the efficiency of pricing policies and of the welfare impacts of toll charges, as it is able to capture their differential effects. More importantly, it shows that low-income commuters may not be significantly worse off with pricing especially when there is a free alternative route. This research demonstrates the need to adopt appropriate analytical techniques and assumptions when modelling the traffic equilibrium in a network with tolls. These include relaxing the homogeneity assumption, examining sensitivity to supply function parameter values and to the effect of vehicle operating cost, and using a route rather than link based measure of consumer surplus

Este trabalho traz uma revisão sobre a evolução da utilização de uma importante ferramenta na gestão da demanda em infraestruturas de transportes: o Congestion Pricing (Tarifação de Congestionamentos). Inicialmente são apresentadas definições de alguns conceitos econômicos básicos que estão relacionados ao sistema estudado, como o custo de oportunidade, demanda, oferta e equilíbrio de mercado. Além desta primeira etapa de revisão, com o objetivo de avaliar como usuários se comportariam diante da implantação de um sistema de cobrança baseado nos níveis de congestionamentos, foram elaborados dois estudos distintos: uma pesquisa exploratória e outra utilizando a técnica da preferência declarada. A pesquisa de caráter exploratório buscou a obtenção de um panorama da atual situação do tráfego na rodovia federal BR-116 (trecho Porto Alegre - Novo Hamburgo) a partir da perspectiva dos usuários de automóveis. Sabe-se que, atualmente, mais de 130.000 veículos passam diariamente pela seção mais carregada desta rodovia, gerando altos níveis de congestionamentos. Neste estudo foram analisados dados como a freqüência com que os usuários trafegam pela rodovia e características das viagens como distâncias, tempos, motivos e horários de saída e retorno. Considerando uma jornada de trabalho de 8 horas por dia, se concluiu que, em média, 25 dias de trabalho são perdidos anualmente com congestionamentos no trecho pesquisado. Sobre valores de tempo, de acordo com a amostra pesquisada, há uma disposição entre os usuários em pagar um valor médio de R$ 0,12 por minuto economizado nos seus deslocamentos. Através da técnica da Preferência Declarada, o segundo estudo aplicado avaliou a probabilidade de usuários alterarem seu comportamento caso fosse adotado um sistema de cobrança variada em função dos níveis de congestionamentos. Utilizando outra amostra da população do mesmo cenário do estudo anterior, foram apresentadas aos usuários situações hipotéticas em que deveriam fazer a opção avaliando, simultaneamente, três variáveis: horário de saída, tempo de deslocamento e descontos na tarifa. Os resultados foram utilizados na calibração de um modelo Logit Binomial e na obtenção de uma função de utilidade linear através do software Stastistical Package for Social Sciences (SPSS). Após a validação do modelo obtido chegou-se à conclusão de que descontos na tarifa e economia de tempo aumentam a probabilidade dos usuários mudarem seus hábitos. Por outro lado, quanto maior a defasagem entre o horário oferecido e o de sua preferência menor a probabilidade desse usuário optar pela troca. Comparados ao primeiro estudo, os valores de tempo encontrados foram mais baixos: R$ 0,09 por minuto economizado (horário de saída) e R$ 0,02 por minuto no tráfego. Os resultados encontrados evidenciam que os usuários têm comportamentos diferentes quando questionados diretamente sobre quanto estariam dispostos a pagar para reduzir seus tempos de deslocamentos ou quando colocada a mesma situação de economia, porém baseada nos descontos na tarifa de congestionamentos. / This work presents a review of developments in the use of an important tool in demand management in transport infrastructure: the Congestion Pricing. Initially are presented some definitions of basic economic concepts that are related to the system studied, such as opportunity cost, supply, demand and market equilibrium. After this first stage of review, in order to assess how users behave facing the adoption of a charging system based on levels of congestion, were drawn up two separate studies: an exploratory study and the other using the stated preference technique. The exploratory research sought to obtain an overview of the current traffic situation in the federal highway BR-116 (between Porto Alegre - Novo Hamburgo) from the perspective of car users. It is known that currently more than 130,000 vehicles pass daily in the heavier section of highway, causing high levels of congestion. This study analyzed data as the frequency with which users travel over the highway and travel characteristics as the distances, times, reasons and times of departure and return. On a workday of eight hours per day, it was concluded that, on average, 25 working days are lost annually to congestion on this stretch. About time values, according to the sample surveyed, there is a willingness among users to pay an average of R$ 0.12 per minute saved in travel. Through Stated Preference technique, the second study applied assessed the likelihood of users to change their behavior if adopted a varied charging system depending on the levels of congestion. Using another sample from the same scenario of the previous study were presented to users hypothetical situations that should make the choice evaluating, simultaneously, three variables: departure time, travel time and fare discounts. The results were used to calibrate a Logit Binomial model and obtaining a linear utility function via software Stastistical Package for Social Sciences (SPSS). After validation of the model obtained, concluded that the discount rate and time savings increase the likelihood that users change their habits. On the other hand, the greater the lag between the offered time and the preferred time the less likely the user choose the time change. Compared to the first study, the time values found were lower: R$ 0,09 per minute saved (departure time) and R$ 0.02 per minute in traffic. The results show that users behave differently when asked directly about how much they are willing to pay to reduce their times of shifts or when placed the same save situation, but based on discounts on congestion pricing.

Este trabalho traz uma revisão sobre a evolução da utilização de uma importante ferramenta na gestão da demanda em infraestruturas de transportes: o Congestion Pricing (Tarifação de Congestionamentos). Inicialmente são apresentadas definições de alguns conceitos econômicos básicos que estão relacionados ao sistema estudado, como o custo de oportunidade, demanda, oferta e equilíbrio de mercado. Além desta primeira etapa de revisão, com o objetivo de avaliar como usuários se comportariam diante da implantação de um sistema de cobrança baseado nos níveis de congestionamentos, foram elaborados dois estudos distintos: uma pesquisa exploratória e outra utilizando a técnica da preferência declarada. A pesquisa de caráter exploratório buscou a obtenção de um panorama da atual situação do tráfego na rodovia federal BR-116 (trecho Porto Alegre - Novo Hamburgo) a partir da perspectiva dos usuários de automóveis. Sabe-se que, atualmente, mais de 130.000 veículos passam diariamente pela seção mais carregada desta rodovia, gerando altos níveis de congestionamentos. Neste estudo foram analisados dados como a freqüência com que os usuários trafegam pela rodovia e características das viagens como distâncias, tempos, motivos e horários de saída e retorno. Considerando uma jornada de trabalho de 8 horas por dia, se concluiu que, em média, 25 dias de trabalho são perdidos anualmente com congestionamentos no trecho pesquisado. Sobre valores de tempo, de acordo com a amostra pesquisada, há uma disposição entre os usuários em pagar um valor médio de R$ 0,12 por minuto economizado nos seus deslocamentos. Através da técnica da Preferência Declarada, o segundo estudo aplicado avaliou a probabilidade de usuários alterarem seu comportamento caso fosse adotado um sistema de cobrança variada em função dos níveis de congestionamentos. Utilizando outra amostra da população do mesmo cenário do estudo anterior, foram apresentadas aos usuários situações hipotéticas em que deveriam fazer a opção avaliando, simultaneamente, três variáveis: horário de saída, tempo de deslocamento e descontos na tarifa. Os resultados foram utilizados na calibração de um modelo Logit Binomial e na obtenção de uma função de utilidade linear através do software Stastistical Package for Social Sciences (SPSS). Após a validação do modelo obtido chegou-se à conclusão de que descontos na tarifa e economia de tempo aumentam a probabilidade dos usuários mudarem seus hábitos. Por outro lado, quanto maior a defasagem entre o horário oferecido e o de sua preferência menor a probabilidade desse usuário optar pela troca. Comparados ao primeiro estudo, os valores de tempo encontrados foram mais baixos: R$ 0,09 por minuto economizado (horário de saída) e R$ 0,02 por minuto no tráfego. Os resultados encontrados evidenciam que os usuários têm comportamentos diferentes quando questionados diretamente sobre quanto estariam dispostos a pagar para reduzir seus tempos de deslocamentos ou quando colocada a mesma situação de economia, porém baseada nos descontos na tarifa de congestionamentos. / This work presents a review of developments in the use of an important tool in demand management in transport infrastructure: the Congestion Pricing. Initially are presented some definitions of basic economic concepts that are related to the system studied, such as opportunity cost, supply, demand and market equilibrium. After this first stage of review, in order to assess how users behave facing the adoption of a charging system based on levels of congestion, were drawn up two separate studies: an exploratory study and the other using the stated preference technique. The exploratory research sought to obtain an overview of the current traffic situation in the federal highway BR-116 (between Porto Alegre - Novo Hamburgo) from the perspective of car users. It is known that currently more than 130,000 vehicles pass daily in the heavier section of highway, causing high levels of congestion. This study analyzed data as the frequency with which users travel over the highway and travel characteristics as the distances, times, reasons and times of departure and return. On a workday of eight hours per day, it was concluded that, on average, 25 working days are lost annually to congestion on this stretch. About time values, according to the sample surveyed, there is a willingness among users to pay an average of R$ 0.12 per minute saved in travel. Through Stated Preference technique, the second study applied assessed the likelihood of users to change their behavior if adopted a varied charging system depending on the levels of congestion. Using another sample from the same scenario of the previous study were presented to users hypothetical situations that should make the choice evaluating, simultaneously, three variables: departure time, travel time and fare discounts. The results were used to calibrate a Logit Binomial model and obtaining a linear utility function via software Stastistical Package for Social Sciences (SPSS). After validation of the model obtained, concluded that the discount rate and time savings increase the likelihood that users change their habits. On the other hand, the greater the lag between the offered time and the preferred time the less likely the user choose the time change. Compared to the first study, the time values found were lower: R$ 0,09 per minute saved (departure time) and R$ 0.02 per minute in traffic. The results show that users behave differently when asked directly about how much they are willing to pay to reduce their times of shifts or when placed the same save situation, but based on discounts on congestion pricing.

Thesis (MTech (Civil Engineering))--Cape Peninsula University of Technology, 2008. / There is an ever increasing need to introduce travel demand measures as the ability to construct new and upgrade existing roads to accommodate additional traffic volumes decreases. The City of Cape Town, hereinafter referred to as the City, has forecasted that traffic in the city could continue to increase by two and a half percent per year. To mitigate against the increased traffic volumes, the City is proposing a number of travel demand strategies, including a park and-ride facilities and high occupancy vehicle initiatives in the short term. The City’s draft travel demand management strategy identifies congestion charging as a measure more possible implementation in the medium term. This study investigates the feasibility of introducing a congestion charge from a traffic engineering perspective. This entails determining if there could be a reduction in traffic entering the Central Business District, what type of congestion charge is most suited for Cape Town and what type of technology is most appropriate at this point in time. In determining the type of charge and technology for introduction in Cape Town, international experience and trials were drawn upon in terms of case studies and research completed. These included developed and developing cities that had either introduced a congestion charge or considered it. To determine the potential level of traffic reduction, transportation elasticities for road pricing/congestion charging were used. This method of calculating the traffic reduction has been used on similar studies and provides a reasonable indication of the potential percentage reduction which could be achieved. The elasticities were based on post-implementation studies undertaken in cities which had introduced a congestion charge or road user pricing. For this study, elasticities between -0.1 and -0.5 were used. The study found that of the types of congestion charging available, a simple cordon charge, around the central business district (CBD) was most feasible. A cordon area would be more appropriate due to the small charge area involved, the flexibility that it allows and because it does not need to be visually intrusive in terms of roadside and enforcement equipment. The location of the cordon area also allows the key roads around the CBD to become the bypass route for vehicles that currently pass through the area. In terms of the charge payment system, it was found that presently, a manual payment system would be more appropriate for the city than a tag and beacon system.

abstract: Cordon pricing strategies attempt to charge motorists for the marginal social costs of driving in heavily congested areas, lure them out of their vehicles and into other modes, and thereby reduce vehicle miles traveled and congestion-related externalities. These strategies are gaining policy-makers` attention worldwide. The benefits and costs of such strategies can potentially lead to a disproportionate and inequitable burden on lower income commuters, particularly those commuters with poor accessibility to alternative modes of transportation. Strategies designed to mitigate the impacts of cordon pricing for disadvantaged travelers, such as discount and exemptions, can reduce the effectiveness of the pricing strategy. Transit improvements using pricing fee revenues are another mitigation strategy, but can be wasteful and inefficient if not properly targeted toward those most disadvantaged and in need. This research examines these considerations and explores the implications for transportation planners working to balance goals of system effectiveness, efficiency, and equity. First, a theoretical conceptual model for analyzing the justice implications of cordon pricing is presented. Next, the Mobility Access and Pricing Study, a cordon pricing strategy examined by the San Francisco County Transportation Authority is analyzed utilizing a neighborhood-level accessibility-based approach. The fee-payment impacts for low-income transportation-disadvantaged commuters within the San Francisco Bay area are examined, utilizing Geographic Information Systems coupled with data from the Longitudinal Employment and Household Dynamics program of the US Census Bureau. This research questions whether the recommended blanket 50% discount for low-income travelers would unnecessarily reduce the overall efficiency and effectiveness of the cordon pricing system. It is proposed that reinvestment of revenue in transportation-improvement projects targeted at those most disproportionately impacted by tolling fees, low-income automobile-dependent peak-period commuters in areas with poor access to alternative modes, would be a more suitable mitigation strategy. This would not only help maintain the efficiency and effectiveness of the cordon pricing system, but would better address income, modal and spatial equity issues. The results of this study demonstrate how the spatial distribution of the toll-payment impacts may burden low-income residents in quite different ways, thereby warranting the inclusion of such analysis in transportation planning and practice. / Dissertation/Thesis / Ph.D. Environmental Design and Planning 2013

Este trabalho traz uma revisão sobre a evolução da utilização de uma importante ferramenta na gestão da demanda em infraestruturas de transportes: o Congestion Pricing (Tarifação de Congestionamentos). Inicialmente são apresentadas definições de alguns conceitos econômicos básicos que estão relacionados ao sistema estudado, como o custo de oportunidade, demanda, oferta e equilíbrio de mercado. Além desta primeira etapa de revisão, com o objetivo de avaliar como usuários se comportariam diante da implantação de um sistema de cobrança baseado nos níveis de congestionamentos, foram elaborados dois estudos distintos: uma pesquisa exploratória e outra utilizando a técnica da preferência declarada. A pesquisa de caráter exploratório buscou a obtenção de um panorama da atual situação do tráfego na rodovia federal BR-116 (trecho Porto Alegre - Novo Hamburgo) a partir da perspectiva dos usuários de automóveis. Sabe-se que, atualmente, mais de 130.000 veículos passam diariamente pela seção mais carregada desta rodovia, gerando altos níveis de congestionamentos. Neste estudo foram analisados dados como a freqüência com que os usuários trafegam pela rodovia e características das viagens como distâncias, tempos, motivos e horários de saída e retorno. Considerando uma jornada de trabalho de 8 horas por dia, se concluiu que, em média, 25 dias de trabalho são perdidos anualmente com congestionamentos no trecho pesquisado. Sobre valores de tempo, de acordo com a amostra pesquisada, há uma disposição entre os usuários em pagar um valor médio de R$ 0,12 por minuto economizado nos seus deslocamentos. Através da técnica da Preferência Declarada, o segundo estudo aplicado avaliou a probabilidade de usuários alterarem seu comportamento caso fosse adotado um sistema de cobrança variada em função dos níveis de congestionamentos. Utilizando outra amostra da população do mesmo cenário do estudo anterior, foram apresentadas aos usuários situações hipotéticas em que deveriam fazer a opção avaliando, simultaneamente, três variáveis: horário de saída, tempo de deslocamento e descontos na tarifa. Os resultados foram utilizados na calibração de um modelo Logit Binomial e na obtenção de uma função de utilidade linear através do software Stastistical Package for Social Sciences (SPSS). Após a validação do modelo obtido chegou-se à conclusão de que descontos na tarifa e economia de tempo aumentam a probabilidade dos usuários mudarem seus hábitos. Por outro lado, quanto maior a defasagem entre o horário oferecido e o de sua preferência menor a probabilidade desse usuário optar pela troca. Comparados ao primeiro estudo, os valores de tempo encontrados foram mais baixos: R$ 0,09 por minuto economizado (horário de saída) e R$ 0,02 por minuto no tráfego. Os resultados encontrados evidenciam que os usuários têm comportamentos diferentes quando questionados diretamente sobre quanto estariam dispostos a pagar para reduzir seus tempos de deslocamentos ou quando colocada a mesma situação de economia, porém baseada nos descontos na tarifa de congestionamentos. / This work presents a review of developments in the use of an important tool in demand management in transport infrastructure: the Congestion Pricing. Initially are presented some definitions of basic economic concepts that are related to the system studied, such as opportunity cost, supply, demand and market equilibrium. After this first stage of review, in order to assess how users behave facing the adoption of a charging system based on levels of congestion, were drawn up two separate studies: an exploratory study and the other using the stated preference technique. The exploratory research sought to obtain an overview of the current traffic situation in the federal highway BR-116 (between Porto Alegre - Novo Hamburgo) from the perspective of car users. It is known that currently more than 130,000 vehicles pass daily in the heavier section of highway, causing high levels of congestion. This study analyzed data as the frequency with which users travel over the highway and travel characteristics as the distances, times, reasons and times of departure and return. On a workday of eight hours per day, it was concluded that, on average, 25 working days are lost annually to congestion on this stretch. About time values, according to the sample surveyed, there is a willingness among users to pay an average of R$ 0.12 per minute saved in travel. Through Stated Preference technique, the second study applied assessed the likelihood of users to change their behavior if adopted a varied charging system depending on the levels of congestion. Using another sample from the same scenario of the previous study were presented to users hypothetical situations that should make the choice evaluating, simultaneously, three variables: departure time, travel time and fare discounts. The results were used to calibrate a Logit Binomial model and obtaining a linear utility function via software Stastistical Package for Social Sciences (SPSS). After validation of the model obtained, concluded that the discount rate and time savings increase the likelihood that users change their habits. On the other hand, the greater the lag between the offered time and the preferred time the less likely the user choose the time change. Compared to the first study, the time values found were lower: R$ 0,09 per minute saved (departure time) and R$ 0.02 per minute in traffic. The results show that users behave differently when asked directly about how much they are willing to pay to reduce their times of shifts or when placed the same save situation, but based on discounts on congestion pricing.

The current Internet architecture presents a barrier to accommodate the vigorous arising demand for deploying new network services and applications. The next-generation architecture views the network virtualization as the gateway to overcome this limitation. Network virtualization promises to run efficiently and securely multiple dedicated virtual networks (VNs) over a shared physical infrastructure. Each VN is tailored to host a unique application based on the user’s preferences. This thesis addresses the problem of the efficient embedding of multiple VNs onto a shared substrate network (SN). The contribution of this thesis are twofold: First, a novel hierarchical SN management framework is proposed that efficiently selects the optimum VN mapping scheme for the requested VN from more than one proposed VN mapping candidates obtained in parallel. In order to accommodate the arbitrary architecture of the VNs, the proposed scheme divides the VN request into smaller subgraphs, and individually maps them on the SN using a variation of the exact subgraph matching techniques. Second, the physical resources pricing policy is introduced that is based on time-ofuse, that reflects the effect of resource congestion introduced by VN users. The preferences of the VN users are first represented through corresponding demand-utility functions that quantify the sensitivity of the applications hosted by the VNs to resource consumption and time-of-use. A novel model of time-varying VNs is presented, where users are allowed to up- or down-scale the requested resources to continuously maximize their utility while minimizing the VNs embedding cost. In contrast to existing solutions, the proposed work does not impose any limitations on the size or topology of the VN requests. Instead, the search is customized according to the VN size and the associated utility. Extensive simulations are then conducted to demonstrate the improvement achieved through the proposed work in terms of network utilization, the ratio of accepted VN requests and the SP profits.

Motivated by the imbalance between demand (i.e., passenger requests) and supply (i.e., available vehicles) in the ride-hailing market and severe traffic congestion faced by modern cities, this dissertation aims to improve the efficiency of the sharing economy by building an agent-based methodological framework for optimal decision-making of distributed agents (e.g., autonomous shared vehicles), including passenger-seeking and route choice. Furthermore, noticing that city planners can impact the behavior of agents via some operational measures such as congestion pricing and signal control, this dissertation investigates the overall bilevel problem that involves the decision-making process of both distributed agents (i.e., the lower level) and central city planners (i.e., the upper level). First of all, for the task of passenger-seeking, this dissertation proposes a model-based Markov decision process (MDP) approach to incorporate distinct features of e-hailing drivers. The modified MDP approach is found to outperform the baseline (i.e., the local hotspot strategy) in terms of both the rate of return and the utilization rate. Although the modified MDP approach is set up in the single-agent setting, we extend its applicability to multi-agent scenarios by a dynamic adjustment strategy of the order matching probability which is able to partially capture the competition among agents. Furthermore, noticing that the reward function is commonly assumed as some prior knowledge, this dissertation unveils the underlying reward function of the overall e-hailing driver population (i.e., 44,000 Didi drivers in Beijing) through an inverse reinforcement learning method, which paves the way for future research on discovering the underlying reward mechanism in a complex and dynamic ride-hailing market. To better incorporate the competition among agents, this dissertation develops a model-free mean-field multi-agent actor-critic algorithm for multi-driver passenger-seeking. A bilevel optimization model is then formulated with the upper level as a reward design mechanism and the lower level as a multi-agent system. We use the developed mean field multi-agent actor-critic algorithm to solve for the optimal passenger-seeking policies of distributed agents in the lower level and Bayesian optimization to solve for the optimal control of upper-level city planners. The bilevel optimization model is applied to a real-world large-scale multi-class taxi driver repositioning task with congestion pricing as the upper-level control. It is disclosed that the derived optimal toll charge can efficiently improve the objective of city planners. With agents knowingwhere to go (i.e., passenger-seeking), this dissertation then applies the bilevel optimization model to the research question of how to get there (i.e., route choice). Different from the task of passenger-seeking where the action space is always fixed-dimensional, the problem of variable action set emerges in the task of route choice. Therefore, a flow-dependent deep Q-learning algorithm is proposed to efficiently derive the optimal policies for multi-commodity multi-class agents. We demonstrate the effect of two countermeasures, namely tolling and signal control, on the behavior of travelers and show that the systematic objective of city planners can be optimized by a proper control.

Congestion charging is a now accepted means of influencing traffic to behave in a more socio-economic optimal way, like e.g. in the Stockholm project. Already early work, in the 1920’s, showed that road use can be inefficient due externalities, i.e. that users don’t experience their own (negative) effect on other users: an extra car on a traffic link causes delays for other cars, but the driver himself does not experience this cost.In the 1950’s it was further shown - for a congested road network with homogeneous users – that if each user is charged a toll equal to the total value of time loss incurred on other users of the network, then -if we have fixed travel demand - this will induce an equilibrium that is system optimal in the sense that the total cost of network usage is minimal (assuming that all users have fixed and identical time values).  But toll charges need to be levied in monetary units, and different travelers have different values of time. Therefore, to account for the effects of tolls, and to be able to compute equilibria, one needs to introduce different user classes, differing in their time values. In this thesis, consisting of four papers, we study congestion pricing of road networks with users differing only in their time values. In particular, we analyze marginal social cost (MSC) pricing, a tolling scheme that charges each user a penalty corresponding to the value of the delays inflicted on other users, as well as its implementation through fixed tolls. Paper III contains the main theoretical work of the thesis. In that paper we show that the variational inequalities characterizing the equilibria in question can be stated in symmetric or non-symmetric forms. The symmetric forms correspond to optimization problems, convex in the fixed-toll case and non-convex in the MSC case, which hence may have multiple equilibria. The objective of the latter problem is the total value of travel time, which thus is minimized at the global optima of that problem. Implementing close-to-optimal MSC tolls as fixed tolls leads to equilibria with possibly non-unique class specific flows, but with identical close-to-optimal values of the total value of travel time. Finally we give an adaptation, to the MSC setting, of the Frank-Wolfe algorithm, which is further applied to some test cases, including Stockholm. Paper I is an early application using Frank-Wolfe, after having realized the possibility to symmetrize the problem. Paper II gives a convexification of non-convex equilibrium problem for MSC tolls. We have used these convexifications to compute lower bounds when computing equilibria. Paper IV is a short note commenting some flaws in two papers by Dial on MSC tolls. / <p>QC 20100610</p>

The number of trips on highways and urban networks has significantly increased in the recent decades in many cities across the world. At the same time, the road network capacities have not kept up with this increase in travel demand. Urban road networks in many countries are severely congested, resulting in increased travel times, increased number of stops, unexpected delays, greater travel costs, inconvenience to drivers and passengers, increased air pollution and noise level, and increased number of traffic accidents. Expanding traffic network capacities by building more roads is extremely costly as well as environmentally damaging. More efficient usage of the existing supply is vital in order to sustain the growing travel demand. Travel Demand Management (TDM) techniques involving various strategies that increase the travel choices to the consumers have been proposed by the researchers, planners, and transportation professionals. TDM helps create a well balanced, less automobile dependent transportation system. In the past, several TDM strategies have been proposed and implemented in several cities around the world. All these TDM strategies, with very few exceptions, are static in nature. For example, in the case of congestion pricing, the toll schedules are previously set and are implemented on a daily basis. The amount of toll does not vary dynamically, with time of day and level of traffic on the highway (though the peak period tolls are different from the off-peak tolls, they are still static in the sense that the tolls don't vary continuously with time and level of traffic). The advent of Electronic Payment Systems (EPS), a branch of the Intelligent Transportation Systems (ITS), has made it possible for the planners and researchers to conceive of dynamic TDM strategies. Recently, few congestion pricing projects are beginning to adopt dynamic tolls that vary continuously with the time of day based on the level of traffic (e.g. I-15 value pricing in California). Dynamic TDM is a relatively new and unexplored topic and the future research attempts to provide answers to the following questions: 1) How to propose and model a Dynamic TDM strategy, 2) What are the advantages of Dynamic TDM strategies as compared to their Static counterparts, 3) What are the benefits and costs of implementing such strategies, 4) What are the travel impacts of implementing Dynamic TDM strategies, and 5) How equitable are the Dynamic TDM strategies as compared to their Static counterparts. This dissertation attempts to address question 1 in detail and deal with the remaining questions to the extent possible, as questions 2, 3, 4, and 5, can be best answered only after some real life implementation of the proposed Dynamic TDM strategies. Two novel Dynamic TDM strategies are proposed and modeled in this dissertation -- a) Dynamic Congestion Pricing and b) Dynamic Highway Space Inventory Control System. In the first part, dynamic congestion pricing, a real-time road pricing system in the case of a two-link parallel network is proposed and modeled. The system that is based on a combination of Dynamic Programming and Neural Networks makes "on-line" decisions about road toll values. In the first phase of the proposed model, the best road toll sequences during certain time period are calculated off-line for many different patterns of vehicle arrivals. These toll sequences are computed using Dynamic Programming approach. In the second phase, learning from vehicle arrival patterns and the corresponding optimal toll sequences, neural network is trained. The results obtained during on-line tests are close to the best solution obtained off-line assuming that the arrival pattern is known. Highway Space Inventory Control System (HSICS), a relatively new demand management concept, is proposed and modeled in the second half of this dissertation. The basic idea of HSICS is that all road users have to make reservations in advance to enter the highway. The system allows highway operators to make real-time decisions whether to accept or reject travellers' requests to use the highway system in order to achieve certain system-wide objectives. The proposed HSICS model consists of two modules -- Highway Allocation System (HAS) and the Highway Reservation System (HRS). The HAS is an off-line module and determines the maximum number of trips from each user class (categorized based on time of departure, vehicle type, vehicle occupancy, and trip distance) to be accepted by the system given a pre-defined demand. It develops the optimal highway allocations for different traffic scenarios. The "traffic scenarios-optimal allocations" data obtained in this way enables the development of HRS. The HRS module operates in the on-line mode to determine whether a request to make a trip between certain origin-destination pair in certain time interval is accepted or rejected. / Ph. D.