Dissertationen zum Thema „Congestion modelling“

Un modèle structurel est fourni afin d'appréhender les phénomènes de capacité dans un modèle d'affectation de flux de voyageurs sur un réseau de transport collectifs. Cela a été fondé sur une représentation du réseau de transports collectifs en deux couches : sur la couche inférieure, le modèle traite séparément chaque sous système du réseau (ligne, station et rabattement) en fonction des effets de capacité spécifiques ; sur la couche supérieure, le choix d'itinéraire d'un voyageur individuel est adressée par une représentation du réseau en leg (ou segment de ligne) en utilisant le coût et les caractéristiques opérationnelles des sous-systèmes respectifs. On établit une cadre novateur pour modéliser les effets de capacité et on développe le modèle CapTA (pour Capacitated Transit Assignment). Il s'agit d'un modèle d'affectation de flux systémique et modulaire. Il adresse les phénomènes de capacité ci dessous : La qualité du service en véhicule est liée au confort de voyageurs à bord. L'occupation d'états de confort hétérogènes (places assises, strapontins et debout à de densités de voyageurs variables) influence la pénibilité perçu du voyage ; La capacité du véhicule à la montée impacte le temps d'attente de voyageurs et leur distribution aux missions disponibles ; La capacité de l'infrastructure de la ligne établit une relation entre le temps de stationnement des véhicules (and par extension les flux de voyageurs en montée et en descente) et la performance des missions et leur fréquence de service. Ces phénomènes sont traités par ligne d'exploitation sur la base d'un ensemble des modèles locaux qui rendent de flux et de coût spécifiques. Par conséquent, ils modifient les conditions locales d'un trajet en transports collectifs pour chaque voyageur individuel. Cependant, ils doivent être adressés dans le cadre d'un réseau de transports collectifs afin de recueillir leur effet sur les choix d'itinéraire sur le réseau ; essentiellement sur les arbitrages économiques qui impactent le choix entre itinéraires alternatifs. Leur traitement sur la couche réseau garantir la cohérence du choix d'itinéraire. Le modèle de station traite de contraintes de capacité spécifiques et évalue les conditions locales de marche, qui est sensible aux interactions des voyageurs à l'intérieur de la station : le goulot instantané à l'entrée d'un élément de circulation retard l'évacuation de la plateforme ; la densité de voyageurs et l'hétérogénéité des leur flux ralenti les voyageurs qui circulent dans une station ; la présence de l'information en temps réel influence le processus de décision des voyageurs. Ces effets n'ont pas seulement un impact sur le choix d'itinéraire à l'intérieure de la station, mais notamment ils modifient les choix de service sur le niveau du réseau. La Région Ile-de-France fournit un champ d'application idéal pour un modèle d'affectation de flux de voyageurs en transport collectifs sous contraintes de congestion. Plus précisément, il est utilisé dans le cadre du modèle CapTA pour illustrer les capacités de simulation et la finesse de l'approche de modélisation adoptée. Le réseau de transports collectifs contient 1 500 missions de cars et autocars, tout comme 260 missions ferroviaires et inclut 14 lignes de métro et 4 lignes de tramway. L'affectation de trafic à l'heure de pointe du matin est caractérisée d'une charge importante en voyageurs sur les sections centrales de lignes ferroviaires qui traversent la ville. Un temps de stationnement élevé, en raison de flux de montée et descente, et la réduction de la fréquence de service impactent la capacité des missions et des lignes. Le temps généralisé d'un trajet est impacté notamment de sa composante de confort à bord. De résultats détaillés sont présentés sur le RER A, la ligne la plus chargée du réseau ferroviaire régional
A structural model is provided to capture capacity phenomena in passenger traffic assignment to a transit network. That has been founded on a bi-layer representation of the transit network : on the lower layer the model addresses each network sub-system (line, station and access-egress) separately, on the basis of specific capacity effects ; on the upper layer a leg-based representation is used with respect to the sub-systems' costs and operating characteristics to address the trip maker's path choices. We establish a novel framework for modelling capacity effects and develop the CapTA network model (for Capacitated Transit Assignment). It is systemic and modular and addresses in particular the following capacity phenomena, the in-vehicle quality of service is linked to the comfort of the passengers on-board. The occupation of heterogeneous comfort states (seats, folding seats and standing at different passenger densities) influences the perceived arduousness of the travel ; the vehicle capacity at boarding influences the waiting time of the passengers and their distribution to the transit services ; the track infrastructure capacity relates the dwelling time of the vehicles (and by extent the alighting and boarding flows) with the performance of the transit services and their service frequency. These phenomena are dealt with by line of operations on the basis of a set of local models yielding specific flows and costs. Accordingly, they modify the local conditions of a transit trip for each individual passenger. However, these should be addressed within the transit network in order to capture their effect on the network path choices; essentially the economic trade-offs that influence the choice between different network itineraries. Their treatment in a network level assures the coherence of the path choice. Equivalently, a station sub-model addresses specific capacity constraints and yields the local walking conditions, sensible to the interaction of the passengers in the interior of a station : the instant bottleneck created at the entry of the circulation elements delays the evacuation of the station platforms; the passenger density and presence of heterogeneous passenger flows slows down the passengers who circulate in the station; and the presence of real-time information influences the decision making process of the transit users exposed to. These effects do not only impact locally the in-station path choice, but most notably they modify the choices of transit routes and itineraries on a network level. The Paris Metropolitan Region provides an ideal application field of the capacity constrained transit assignment model. It is mainly used as a showcase of the simulation capabilities and of the finesse of the modelling approach. The transit network involves 1 500 bus routes together with 260 trains routes that include 14 metro lines and 4 light rail lines. Traffic assignment at the morning peak hour is characterized by heavy passenger loads along the central parts of the railway lines. Increased train dwelling, due to boarding and alighting flows, and reduction in the service frequency impact the route and the line capacity. The generalized time of a transit trip is impacted mainly though its in-vehicle comfort component. Detailed results have been provided for the RER A, the busiest commuter rail line in the transit network

“Störningsfri stad” is an ongoing research project in Norrköping with the aim to create a planning system that shows the impact on the city caused by construction project related logistic activities. Based on the general idea that construction sites create disturbances within a city the thesis evaluates how it is possible to model excess congestion caused by construction transport and trips. Other part of thesis focuses of the application of construction logistic solutions and their respective impact on the congestion. To deal with the stated problem, a case is created – Case Norrköping. It involves the preparation of datasets that describe travel patterns for HGV and workers going to and from construction sites. Case Norrköping is based on six construction sites located in Norrköping. Construction sites have an estimated demand of transports. For that reason, three reference values are created. Reference values are given as the number of HGV serving all sites – 152, 458, 1404 number of vehicles during one working day. To create OD-matrices for the HGV trips, six supplier locations are used. Resulting datasets describe in detail how and when HGV and workers arrive at the construction sites. The actual modelling of congestion effects is done in traffic simulation framework MATSim. An existing Norrköping MATSim model is used and combined with the datasets created in Case Norrköping. Output of simulation is potential congestion effect on car traffic in Norrköping. Case Norrköping is evaluated by changing the number of involved sites. Results show that construction transports contribute to increased congestion levels. Absolute increase of congestion is not significant for scenario 152 HGV. Scenarios 458 and 1404 HGV do show noticeable increases in congestion, especially during peak hour periods. Finally, construction logistic solutions are applied to Case Norrköping to evaluate the impact on congestion level. Different HGV arrival schedules at construction sites are applied. Result of logistic solution application shows that congestion levels can be decreased if peak-hour avoidance is considered in construction transport planning. Even constant arrival rate compared to present arrival rate in Case Norrköping can provide a minor decrease in congestion levels. The gains of applying logistic become more distinct with larger number of HGV. At high HGV demand such as scenario 1404 HGV, total delay hours can be decreased between 20 and 40 percent with a suitable construction logistic solution.

Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet

The equity effect of congestion pricing has been advocated to be given enough concern for its acceptability. This thesis aimed to explore the mixed effects in travel behaviour changing caused by congestion charging in demography factors (social economic status) and context factors (location, flexibility, access to car and possession of long-term public transport card). In order to understand by what mechanisms congestion pricing affects the equity, structural equation modelling was applied to model the causal networks in the case study of Stockholm congestion charge. Results revealed a more complicated influence from different combination of factors. The location relative to charging cordon mattered for the trip-making both directly and indirectly through the transport mode preference. The work schedule flexibility should be also taken into consideration when considering the time-based scheme. The mixed effects between two groups of factors suggested that more factors should be considered when justifying the privileged group and disadvantaged group to implement the policy. The method used in this thesis could be very constructive for equity effect evaluation in other cities with different conditions.

Many-particle systems with congestion are widely found in biology, for example, in cell tissues or herds. Mathematical modelling constitutes an important tool in their study. In contrast to common approaches, we propose two new modelling frameworks that rely on the exact treatment of the contacts between particles: a particle-based and a continuum framework. Both frameworks are based on the same behavioural rules, namely 1) two particles cannot overlap with each other and 2) the particles seek a minimum of a given confining potential at all times. The dynamics is driven by the evolution of the potential and changes in particle characteristics, such as size. In the first part, the static equilibria of the particle-based model are obtained as solutions to a minimization problem. This leads to non-convex optimization under volume exclusion constraints. Classical tools are either not applicable or not efficient. We develop and study a new and efficient minimization algorithm to approximate a solution. The second part concerns the time-evolution of the particle-based framework. We develop new time-stepping schemes involving the resolution of a minimization problem at each time-step, which is tackled with the minimization algorithm developed in the first part. The study of these schemes is performed in the case of a system of hard-spheres undergoing ballistic aggregation on a torus and it succeeds to simulate up to one million particles. These new tools are applied to the study of the mechanics of a cell tissue, which has allowed to validate them in practice. In the third part, we develop a continuum modelling framework describing the evolution of particle density. Our approach differs from previous ones by relying on different modelling assumptions that are more appropriate to biological systems. We show that this novel approach leads to a free-boundary problem and we characterize the dynamics of the boundary.

The level of air pollution in urban areas, which is largely affected by road traffic, is an issue of high political relevance. Congestion is most prevalent in urban areas and a common and increasingly present phenomenon worldwide. The first four chapters of this study have investigated how and to what extent models, which are used to predict emissions on road links in urban road networks, include the effects of congestion on emissions. In order to make this assessment, traffic engineering literature and empirical studies have been examined and used as a basis to review (current) emission models that exist or have been used around the world. Congestion causes changes in driving patterns of individual vehicles in a traffic stream, and these changes are subsequently reflected in changes in congestion indicators and changes in emission levels. This consideration and a literature review has led to a proposed 'congestion typology' of emission models, which reflects the different ways in which and the extent to which congestion has been incorporated in these models. The typology clarifies that six of in total ten families of emission models that were investigated in this thesis explicitly consider congestion in the modelling process (i.e. model variables are related to congestion), although this is done in different ways. For the remaining four families of emission models it was not possible to determine the extent to which congestion has been incorporated on the basis of literature review alone. Two families fell beyond the scope of this work since they cannot be used to predict emission on road links. For the other two families it became clear in the course of the thesis that the extent can be determined through analysis of driving pattern data (and other information with respect to e.g. data collection) that were used in the model development. A new methodology is presented in this thesis to perform this analysis and to assess the mean level of congestion in driving patterns (driving cycles). The analysis has been carried out for one important family of emission models, the so-called travel speed models ('average speed models'), which are used extensively in urban network modelling. For four current models (COPERT III, MOBILE 6, QGEPA 2002, EMFAC 2000), it is concluded that these models implicitly (i.e. congestion is inherently considered) take varying levels of congestion into account, but that this conclusion is subject to a number of limitations. It became clear in the course of this study that prediction of (the effects of) congestion in both traffic models and emission models is generally restricted to certain modelling dimensions. As a consequence, the effects of congestion are only partially predicted in current air emission modelling. Chapter 5 has attempted to address the question whether congestion is actually an important issue in urban network emission modelling or not. It also addressed the question if different types of emission models actually predict different results. On the basis of a number of selection criteria, two types of models were compared, i.e. one explicit model (TEE-KCF 2002) and two implicit models (COPERT III, QGEPA 2002). The research objectives have been addressed by applying these emission models to a case-study urban network in Australia (Brisbane) for which various model input attributes were collected from different sources (both modelled and field data). The findings are limited by the fact that they follow from one urban network with particular characteristics (fleet composition, signal settings, speed limits) and application of only a few particular emission models. The results therefore indicate that: 1. Changes in traffic activity (i.e. distribution of vehicle kilometres travelled on network links) over the day appear to have the largest effect on predicted traffic emissions. 2. Congestion is an important issue in the modelling of CO and HC emissions. This appears not to be the case for NOx emissions, where basic traffic composition is generally a more important factor. For the most congested parts in the urban network that have been investigated, congestion can more than double predicted emissions of CO and HC. 3. Different types of emission models can produce substantially different results when absolute (arithmetic) differences are considered, but can produce similar results when relative differences (ratio or percent difference) are considered.

Motivated by the desire to explore future traffic flows that will consist of a mixture of classical vehicles and vehicles equipped with advanced driver assistance systems, new mathematical theories and models are developed. The basis for this theory was borrowed from the kinetic description of gas flows, where we replaced the behaviour of the molecules by typical human driving behaviour. From a methodological point of view, this 'human-kinetic' traffic flow theory provides two major improvements with respect to existing theory. Firstly, the model builds exclusively on a mathematical description of individual driver behaviour, whereas traditionally field measurements of traffic flow variables like flow rate and average speed of the flow are needed. This is of major importance for the exploration of future traffic flows with vehicles and equipment that are not yet on the market, and for which at best individual test results from driving simulator experiments or small scale field trials are available. Secondly, the model accounts for the more refined aspects of individual driver behaviour by considering the 'internal' state of the driver (active/passive, aware/unaware,...) and the variations of driving strategy that occur during driving. This is important when the ambition is to capture refined congestion patterns like the occurrence of stop-and-go waves, oscillating congestion and long jams, where the driving strategy may depend for instance on the motivation of the driver to follow closely. This new theory links together the worlds of traffic engineers and behavioural scientists. As such, it is a promising tool that increases the insight in the human behaviour as a basis of various dynamic congestion patterns, and it facilitates the design and evaluation of electronic systems in the vehicle that assist the driver to behave safer, more comfortable and more efficient in busy traffic flows. Herewith, the results of this research are relevant, both for the theoretical interest of the TRAIL research school, and for the more practically oriented work of TNO, who provided financing for this research in the joint T3 research program.

Congestion charging has drawn considerable attention of transport analysts and policymakers as a mean of relieving urban traffic congestion. Proper prediction of the impacts of charging is necessary for policy makers to take right decisions. A European project named SILVERPOLIS have been introduced in this connection to describe state-of-practice in modelling effects of congestion charging and to identify features of transport models that are crucial for reliable forecasting of effects of congestion charging. This master thesis is a part of the SILVERPOLIS project, where Stockholm congestion charging scheme has been analysed using two different types of dynamic simulators: METROPOLIS and SILVESTER. The simulations are based on traffic data collected before and after the Stockholm congestion charging trial performed in spring 2006. The result of simulation suggests that METROPOLIS, which has been used for predicting effects of congestion charging in Ile-de-France, manages well to forecast the consequences of congestion charging for Stockholm. Comparison with SILVESTER model disclosed that, although calibration results of the two models differs in some respect, both models give similar results regarding impacts of congestion charging. The different modelling features and assumptions have been described for the two models. Despite the fact that the two models vary a lot in their assumptions and modelling style, both of them has proved to be good at describing the effect of congestion charging.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011.
ENGLISH ABSTRACT: An investigation is made to find a suitable routing protocol for a millimeter wave ad hoc wireless network. It is discovered that a hierarchical routing protocol is ideal for a high node density. Due to the high bandwidth that is possibly available, with millimeter wave transmission, packets are used to keep links between nodes active and to control data packet congestion. Cluster leaders are elected and use token packets to provide nodes with more queued messages with more transmission chances, assisting the network in congestion control. Hello messages are sent frequently to keep routing information at nodes fresh and to detect broken links quickly. If a broken link is found a new route is readily available, within a second. A simulation is created to test the protocol. Changes are made to the original proactive cluster routing protocol to reduce the route length and lessen routing overhead. A theoretical model is developed to estimate the mean waiting time for a packet. Although insight is gained by modelling the latency with queueing theory it is suggested, due to the protocol’s complexity, to use other mathematical modelling techniques such as a Markov state model or a Petri net.
AFRIKAANSE OPSOMMING: Ondersoek word ingestel na ’n geskikte roete protokol vir ’n millimeter golflengte ad hoc radio pakkie netwerk. Daar word gevind dat ’n hi¨erargiese kluster roete protokol ideaal is vir ’n ho¨e digtheid van nodusse. As gevolg van die ho¨e bandwydte, wat moontlik beskikbaar is met millimeter golflengte transmissie, word pakkies gebruik om kommunikasie skakels tussen nodes in stand te hou en data pakkie verkeersopeenhoping te beheer. Kluster leiers word verkies en gebruik teken-pakkies om nodes met ’n groter data pakkie las meer transmissie kanse te gee. Sodoende word die verkeersopeenhoping van data pakkies verminder. Hallo pakkies word gereeld gestuur om die roete inligting vars te hou en gebroke kommunikasie skakels vinnig op te spoor. As ’n gebroke skakel gevind word, word ’n alternatiewe roete vinnig opgestel, binne ’n sekonde. ’n Simulasie word opgestel om die protokol te toets. Veranderinge aan die oorspronklike proaktiewe kluster protokol word aangebring om roete lengte te verklein en oorhoofse roete inligting kommunikasie te verminder. ’n Teoretiese model gebasseer op tou-staan teorie word ontwikkel om die wagtyd van ’n pakkie te bepaal. Alhoewel, insig verkry is deur die protokol te analiseer deur middel van tou-staan teorie, word daar voorgestel, as gevolg van die protokol se kompleksiteit, om eerder ander wiskundige modelleeringstegnieke te gebruik soos ’n Markov toestands model of ’n Petri net.

Depuis une vingtaine d'années, les problématiques de transport public en région parisienne sont devenues une préoccupation majeure. Pour les usagers qui consacrent en moyenne environ deux heures quotidiennement à leurs déplacements domicile-travail, la qualité de l'offre de transport est un enjeu majeur.La société nationale des chemins de fer français qui exploitent la majeure partie du réseau ferré dans cette région joue un rôle central dans l'organisation des transports. Mais à l'opposé des attentes qui pèsent sur ce secteur, le trafic ferroviaire rencontrent un certain nombre de dysfonctionnements. En s'inscrivant dans une démarche globale de remise en question des principes d'exploitation ferroviaire en zone dense, cette thèse apporte un regard nouveau sur l'origine des retards qui affectent les trains.Un modèle simple qui permet d'étudier la congestion du trafic ferroviaire sous l'influence de perturbations aléatoires est proposé. En s'inspirant des outils du trafic routier et tout particulièrement du diagramme fondamental de réseau,on définit pour le ferroviaire, le diagramme fondamental de ligne ferroviaire qui permet de représenter le débit en fonction de la concentration sur une portion de ligne ferroviaire. Cet outil est ensuite utilisé pour comparer les résultats issus de notre modèle à un jeu de données mesuré sur deux lignes de chemin de fer de la région parisienne.Cette comparaison montre que notre modèle permet de reproduire qualitativement les phénomènes de congestion du trafic observés sur les cas réels
Over the last twenty years, public transport issues in the Paris region have become a major concern. The French national railway company, which operates most of the rail network in this region, plays a central role in the organisation of transport. However, in contrast to expectations in this sector, rail traffic is experiencing a number of malfunctions. As part of an overall approach to questioning the principles of rail operation in dense areas, this thesis provides a new look at the origin of delays affecting trains. Drawing on road traffic tools and in particular the basic network diagram, the basic railway line diagram is defined for railways, which makes it possible to represent the flow as a function of concentration on a portion of a railway line. This tool is then used to compare the results from our model with a set of data measured on two railway lines in the Paris region, which shows that our model can qualitatively reproduce the traffic congestion phenomena observed on real cases.(Translated with www.DeepL.com/Translator)

This thesis consists of two parts, and the connection between them is the so-called Wardrop's equilibrium. In the rst part of this thesis, which is the theoretical part, we study the congested transport dynamics arising from a non-autonomous tra c optimization problem. In this setting, we prove one can nd an optimal tra c strategy with support on the trajectories of a DiPerna-Lions ow. The proof follows the scheme introduced by Brasco, Carlier and Santambrogio in the autonomous setting, applied to the case of supercritical Sobolev dependence in the spatial variable. This requires both Lipschitz and weighted Sobolev apriori bounds for the minimizers of a class of integral functionals whose ellipticity bounds are satis ed only away from a ball of the gradient variable. We are then able to nd the con guration of Wardrop's equilibrium. In the second part of this thesis, which is the practical part, we use the established Wardrop's equi- librium in the theoretical section, in order to optimize the tra c problem in rel-life application. New OD demand problem formulation is explored which allows the modeler to de ne structural similarity between the historical and estimated OD matrix while ensuring computationally fast and tractable solution. Shrinkage regression methods, such as Ridge and Lasso regression, are proposed to de ne distance function between historical and estimated OD matrix, in order to minimize estimation vari- ance, and ensure the estimated OD matrix is close to true value. The presented OD estimation models reduce dimensionality of the OD demand vector, which is crucial when the dimensionality of OD ma- trix is high, due to high level of zoning system. A new solution approach based on the well-known gradient descent algorithm is applied to solve the proposed models. Finally, results are tested out on a real life-size network.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that have
Ministry of Higher Education in Egypt and the Egyptian Cultural Centre and Educational Bureau in London

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that have.

A Cognitive Radio Network (CRN) is a technology that allows unlicensed users to utilise licensed spectrum by detecting an idle band through sensing. How- ever, most research studies on CRNs have been carried out without considering the impact of sensing on the performance and security of CRNs. Sensing is essential for secondary users (SUs) to get hold of free band without interfering with the signal generated by primary users (PUs). However, excessive sensing time for the detection of free spectrum for SUs as well as extended periods of CRNs in an insecure state have adverse effects on network performance. Moreover, a CRN is very vulnerable to attacks as a result of its wireless nature and other unique characteristics such as spectrum sensing and sharing. These attacks may attempt to eavesdrop or modify the contents of packets being transmitted and they could also deny legitimate users the opportunity to use the band, leading to underutilization of the spectrum space. In this context, it is often challenging to differentiate between networks under Denial of Service (DoS) attacks from those networks experiencing congestion. This thesis employs a novel Stochastic Activity Network (SAN) model as an effective analytic tool to represent and study sensing vs performance vs security trade-offs in CRNs. Specifically, an investigation is carried out focusing on sensing vs security vs performance trade-offs, leading to the optimization of the spectrum band’s usage. Moreover, consideration is given either when a CRN experiencing congestion and or it is under attack. Consequently, the data delivery ratio (PDR) is employed to determine if the network is under DoS attack or experiencing congestion. In this context, packet loss probability, queue length and throughput of the transmitter are often used to measure the PDR with reference to interarrival times of PUs. Furthermore, this thesis takes into consideration the impact of scalability on the performance of the CRN. Due to the unpredictable nature of PUsactivities on the spectrum, it is imperative for SUs to swiftly utilize the band as soon as it becomes available. Unfortunately, the CRN models proposed in literature are static and unable to respond effectively to changes in service demands. To this end, a numerical simulation experiment is carried out to determine the impact of scalability towards the enhancement of nodal CRN sensing, security and performance. Atthe instant the band becomes idle and there are requests by SUs waiting for encryption and transmission, additional resources are dynamically released in order to largely utilize the spectrum space before the reappearance of PUs. These additional resources make the same service provision, such as encryption and intrusion detection, as the initial resources. To this end,SAN model is proposed in order to investigate the impact of scalability on the performance of CRN. Typical numerical simulation experiments are carried out, based on the application of the Mobius Petri Net Package to determine the performance of scalable CRNs (SCRNs) in comparison with unscalable CRNs (UCRNs) and associated interpretations are made.

Context. Due to increase in demand for RORO shipping services,the RORO terminal gate system need to handle more number of vehicles for every RORO vessel departure. Therefore, various congestion problems can occur; so, to address all possible congestion related problemsat RORO terminal, terminal gate systems are implemented with advanced technologies and updated to full or partial functioning automated gate systems. Objectives. In this research study considering the future increase in demand for wheeled cargo shipping, we attempt to propose a solution for reducing congestion and investigating optimal positions for each automated gate system service at RORO port terminal. Methods. In this Master thesis, as part of qualitative study we conduct a literature review and case study to know about the existing related work on this research problem and know about the real world system operation and behaviour of a RORO terminal gate system.Later, applying the adequate knowledge acquired from above mentioned qualitative studies, we perform a discrete event simulation experiment using Anylogic® professional 7.02 simulation software to address defined research objectives. Results. Considering the peak and low periods of present and future estimated demand volumes as different scenarios,various simulation experiment results are generated for different key performance indicators. The result values of these key performance indicators address various research objectives. Conclusions. This research study finally concludes that, the average queue length values at each automated gate system service implicates optimal position for each service and directly address the congestion problem. We also conclude that in every estimated increase in vehicles attending the RORO terminal, assigning optimal arrival time windows for respective vehicle types minimizes the congestion problem at automated gate system.

Cette thèse porte sur les modèles d'équilibre dynamique sur un réseau de transport et de leurs applications à l'affectation de trafic. Elle vise à proposer une formulation à la fois générale, mathématiquement rigoureuse et microéconomiquement cohérente de l'équilibre dynamique. Une attention toute particulière est accordée à la représentation de la demande de transport et plus spécifiquement à la modélisation des hétérogénéités dans les préférences des usagers du réseau, ainsi que de leurs stratégies de choix d'horaires dans leurs déplacements. Tout d'abord nous exprimons l'équilibre dynamique comme un jeu de Nash avec un continuum de joueurs. Cette formulation nous permet d'obtenir un résultat d'existence. Celui-ci s'applique notamment au plus simple des modèles d'équilibre dynamique, où les usagers sont identiques et ne choisissent pas leurs horaires de départ. Ensuite, nous présentons deux modèles d'équilibre pour lesquels une solution analytique peut être établie. Le premier est une généralisation du modèle de goulot de Vickrey. Alors que Vickrey considère une distribution des horaires préférés d'arrivée en forme de S, nous traitons de distributions quelconques. Le deuxième modèle proposé est un réseau à péage avec deux routes et des usagers dont la valeur du temps est distribuée. Ce modèle nous permet d'investiguer les efficacités relatives de différentes stratégies de tarification et de voir comment celles-ci sont affectés par le niveau d'hétérogénéité dans la valeur du temps. Pour finir, un modèle calculable est présenté et des méthodes de résolution sont proposées. Le modèle est testé sur le réseau routier national. Par ailleurs, il est exploité pour tester une tarification modulée en fonction du temps dont l'objectif est d'atténuer la congestion lors des grands départs de vacances
This thesis is focused on dynamic user equilibrium (DUE) models and theirapplications to traffic assignment. It aims at providing a mathematically rigorous and general formulation for the DUE. Particular attention is paid to the representation of transport demand and more specifically to trip scheduling and users with heterogeneous preferences.The DUE is first expressed as a Nash game with a continuum of players. It strongly relies on up-to-date results from mathematical economics. This formulation allows to prove an existence result for DUE. This results notably applies to one of the simplest dynamic user equilibrium model, where users are homogeneous and departure time choice is not allowed.Then, two simple DUE models for which the solutions can be derived analytically are presented. The first one is a generalization of the Vickrey's bottleneck model. Whereas Vickrey assumed that the distribution of preferred arrival time is S-shaped, we consider more general distributions. In the second model, we have a two-route tolled network where users are continuously heterogeneous with respect to their value of time. This allows us to conduct a study on the relative efficiencies of various pricing strategy and how it is affected by the level of heterogeneity in users' value of time.Finally, a computable model is designed and corresponding solution methods are proposed. A test on the french national road network is conducted. The model is used to assess an hypothetical time-varying pricing scheme intended to ease summer traffic congestion

Les conditions de circulation sur un réseau routier subissent souvent de la congestion. Selon ses sources, la congestion routière peut être classée en deux catégories : la congestion récurrente déterminée par les lois de trafic et la congestion non-récurrente due aux incidents, accidents ou autres aléas sur la route. Grâce à l'avancement des technologies, notamment en informatique, communication et techniques de traitement des données, l'exploitant est devenu capable de détecter les perturbations, de mesurer les effets et même d'anticiper l'état du trafic afin de mieux adapter ses actions d'exploitation. L'information dynamique concernant les conditions de trafic permet aux usagers de réduire l'inconfort et d'effectuer leur choix d'itinéraire de manière plus raisonnable. Pour l'exploitant, le service d'information aux usagers peut servir à la gestion du trafic. Nous avons étudié la contribution potentielle de l'information dynamique au profit individuel des usagers et à la performance collective du système en prenant en compte : i) la congestion récurrente et non-récurrente ; ii) des différents comportements de choix d'itinéraire en fonction de l'accessibilité à l'information ; iii) d'autres actions de gestion du trafic menées par l'exploitant. Un modèle théorique avec une application analytique sur un réseau élémentaire de deux routes parallèles, une paire origine-destination et deux classes d'usagers respectivement informée ou non-informée nous a permis de retirer de nombreuses indications : i) la diffusion excessive de l'information avec un contenu " neutre " dégrade à la fois le profit individuel et la performance du système ; ii) l'information dynamique avec certain contenu " coopératif " peut contribuer l'optimisation du système sans causer le problème d'acceptabilité ; iii) l'information dynamique et d'autres mesures de gestion dynamique s'interagissent de manière complémentaire à l'optimisation du trafic

Since the field of computer networks has rapidly grown in the last two decades, congestion control of traffic loads within networks has become a high priority. Congestion occurs in network routers when the number of incoming packets exceeds the available network resources, such as buffer space and bandwidth allocation. This may result in a poor network performance with reference to average packet queueing delay, packet loss rate and throughput. To enhance the performance when the network becomes congested, several different active queue management (AQM) methods have been proposed and some of these are discussed in this thesis. Specifically, these AQM methods are surveyed in detail and their strengths and limitations are highlighted. A comparison is conducted between five known AQM methods, Random Early Detection (RED), Gentle Random Early Detection (GRED), Adaptive Random Early Detection (ARED), Dynamic Random Early Drop (DRED) and BLUE, based on several performance measures, including mean queue length, throughput, average queueing delay, overflow packet loss probability, packet dropping probability and the total of overflow loss and dropping probabilities for packets, with the aim of identifying which AQM method gives the most satisfactory results of the performance measures. This thesis presents a new AQM approach based on the RED algorithm that determines and controls the congested router buffers in an early stage. This approach is called Dynamic RED (REDD), which stabilises the average queue length between minimum and maximum threshold positions at a certain level called the target level to prevent building up the queues in the router buffers. A comparison is made between the proposed REDD, RED and ARED approaches regarding the above performance measures. Moreover, three methods based on RED and fuzzy logic are proposed to control the congested router buffers incipiently. These methods are named REDD1, REDD2, and REDD3 and their performances are also compared with RED using the above performance measures to identify which method achieves the most satisfactory results. Furthermore, a set of discrete-time queue analytical models are developed based on the following approaches: RED, GRED, DRED and BLUE, to detect the congestion at router buffers in an early stage. The proposed analytical models use the instantaneous queue length as a congestion measure to capture short term changes in the input and prevent packet loss due to overflow. The proposed analytical models are experimentally compared with their corresponding AQM simulations with reference to the above performance measures to identify which approach gives the most satisfactory results. The simulations for RED, GRED, ARED, DRED, BLUE, REDD, REDD1, REDD2 and REDD3 are run ten times, each time with a change of seed and the results of each run are used to obtain mean values, variance, standard deviation and 95% confidence intervals. The performance measures are calculated based on data collected only after the system has reached a steady state. After extensive experimentation, the results show that the proposed REDD, REDD1, REDD2 and REDD3 algorithms and some of the proposed analytical models such as DRED-Alpha, RED and GRED models offer somewhat better results of mean queue length and average queueing delay than these achieved by RED and its variants when the values of packet arrival probability are greater than the value of packet departure probability, i.e. in a congestion situation. This suggests that when traffic is largely of a non bursty nature, instantaneous queue length might be a better congestion measure to use rather than the average queue length as in the more traditional models.

Nell'ultimo decennio, un notevole interesse nell'ambito della modellizzazione del traffico si è sviluppato attorno al concetto dei Diagrammi Fondamentali Macroscopici (MFD), resi popolari da un celebre esperimento condotto nel 2008 nella città giapponese di Yokohama. Tali diagrammi mettono in relazione le medie spaziali di flusso, densità e velocità su un intero network stradale e risultano sotto certe condizioni una proprietà intrinseca di quest'ultimo, indipendente dalla domanda di mobilità degli utenti, costituendo così potenzialmente un importante strumento nel controllo dinamico del traffico. Il presente lavoro si propone quindi di indagare l'esistenza di MFD in un network extraurbano attorno alla città di Bologna, composto sia da tratti di autostrada e tangenziale che da strade statali e provinciali. I diagrammi sono stati costruiti utilizzando una simulazione di traffico sulla regione Emilia-Romagna, basata su un input di dati di mobilità provenienti da utenti della rete TIM che consentono di ricavare su base oraria gli spostamenti aggregati dei veicoli. Se il carico è sufficientemente alto, si osserva negli MFD l'emergere di fenomeni di isteresi, a causa dei quali si trovano a parità di densità media valori differenti di flusso e velocità. Le cause dell'isteresi sono quindi analizzate nel dettaglio studiando gli effetti della congestione sulla variabilità spaziale della densità, che risulta essere un fattore chiave insieme all'eterogeneità della rete nella forma dei diagrammi.

Transport investments and policies are increasingly turned towards dealing with transport congestion rather than with shortening the potential free flow travel time. However, appraisal methodologies for projects meant to reduce congestion are relatively less well developed compared to methodologies for projects aiming to reduce travel times. Static assignment models are for instance incapable of predicting the build-up and dissipation of traffic queues and capturing the experienced crowding caused by uneven on-board passenger loads. Despite of the availability of dynamic traffic assignment and despite of fairly concrete ideas of how integration with demand models could take place, only few model systems have been developed for real applications. The predicted reduction of traffic volume across the Gothenburg congestion charge cordon in the peak, 11%, turned out to be an accurate estimate of the observed reduction, 12%. The reduction in the off-peak, however, was overpredicted, as it was also in the Stockholm case. To analyse congestion charges in Stockholm it is necessary and fully possible to integrate DTA with the demand model. In the performed tests it could be seen that both tested models had problems replicating the flow on the main bypass early in the morning but otherwise performed well. A case study of a metro extension in Stockholm demonstrated that congestion effects constitute more than half of the total benefits and that these effects are excessively underestimated by a conventional static model. Effects of various operational measures can be analysed with BusMezzo and the results have been validated against observed data. The findings indicate that all three tested measures in a case study (boarding through all doors, headway-based holding and bus lanes) had an overall positive impact on service performance and that there are synergetic effects. Using a continuous VTT distribution and hierarchical route choice was demonstrated as a successful method of modelling the multi-passage rule implemented in Gothenburg congestion charges and was shown to give realistic predictions of route choice effects. First results from integration of DTA with a travel demand model for the Stockholm region show that even without systematic calibration the DTA is in reasonable agreement with observed traffic counts and travel times. The presented experiments did not reveal a striking difference between using a macroscopic and a microscopic assignment package. While travel time savings are often the only benefit included in public transport project appraisals, the best practice assigns weighted value of time to average load/capacity measures. However, failure to represent dynamic congestion effects may lead to substantial underestimation of the benefits of projects primarily designed to increase capacity rather than reduce travel times. The impact of small operational measures should not be underestimated. These measures are relatively cheap compared to investments in new transit infrastructure and large societal gains can therefore be achieved by their implementation.
Investeringar och åtgärdsprogram inom transportområdet handlar allt oftare om att råda bot på trängsel snarare än att minska potentiella friflödesrestider. Utvärderingsmetoder för projekt som syftar till att minska trängsel är dock mindre utvecklade än metoder för projekt som syftar till att minska restider. Statiska nätutläggningsmodeller är till exempel inte lämpade för att prognosera uppbyggnad och avveckling av köer eller för att fånga upplevd trängsel orsakad av ojämn belastning på kollektivtrafikfordon. Trots förekomsten av dynamisk trafikutläggning och trots tämligen konkret kunskap om hur integration med efterfrågemodeller kunde gå till, finns det endast ett fåtal modellsystem utvecklade för verklig tillämpning. Den predikterade trafikflödesminskningen på 11 % över trängselskattesnittet i Göteborg visade sig stämma väl överens med den observerade minskningen på 12 %. Minskningen under lågtrafik visade sig dock vara överskattad, precis som i Stockholmsfallet. För att analysera trängseleffekter i Stockholm är det nödvändigt och fullt möjligt att integrera en DTA-modell med efterfrågemodellen. I de utförda testerna observerades att båda de testade modellerna hade problem med att återskapa korrekta flöden på Essingeleden under morgonens maxtimme, men i övrigt gav god överensstämmelse. I en fallstudie av blå tunnelbanelinjes förlängning i Stockholm visade det sig att trängseleffekter utgjorde mer än hälften av de totala nyttorna och att dessa effekter är kraftigt underskattade i en konventionell statisk modell. Effekter av olika operationella åtgärder kan analyseras med BusMezzo och resultaten har blivit validerade mot observerade data. Resultaten tyder på att alla tre testade åtgärder i en fallstudie (ombordstigning i alla dörrar, turtäthetsbaserad reglering och busskörfält) hade en positiv inverkan på servicenivån och att det förekommer synergieffekter dem emellan. Användandet av kontinuerlig tidsvärdesfördelning och hierarkiskt ruttval har framgångsrikt demonstrerats som en metod för att modellera flerpassageregeln i Göteborgs trängselskattesystem och visade sig ge realistiska prediktioner av ruttvalseffekter. De första resultaten från integrationen DTA i efterfrågemodellen för Stockholmsregionen visar att även utan systematisk kalibrering är modellresultaten i paritet med observerad trafikflöden och restider. Experimentresultaten tyder inte på någon slående skillnad mellan att använda makroskopisk eller mikroskopisk nätutläggning. Restidsvinst är ofta är den enda nyttan som ingår i nyttokalkylen för kollektivtrafikinvesteringar, men i visa fall är det befogat att använda viktade tidsvärden beroende på förhållandet belastning / kapacitet. Att inte modellera dynamiska trängseleffekter kan dock leda till påtagbar underskattning av nyttorna i projekt som primärt handlar om kapacitetshöjning snarare än restidsförkortning. Nyttan av små operationella åtgärder ska inte underskattas. Dessa åtgärder är oftast relativt billiga jämfört med investeringar i ny transportinfrastruktur och stora sociala nyttor kan därför åstadkommas.

QC 20150601

Appraisal methodologies for congestion mitigation projects are relatively less well developed compared to methodologies for projects reducing free flow travel times. For instance, static assignment models are incapable of representing the build-up and dissipation of traffic queues, or capturing the experienced crowding caused by uneven on-board passenger loads. Despite the availability of dynamic traffic assignment, only few model systems have been developed for cost-benefit analysis of real applications. The six included papers present approaches and tools for analysing traffic and transit projects where congestion relief is the main target. In the transit case studies, we use an agent-based simulation model to analyse congestion and crowding effects and to conduct cost-benefit analyses. In the case study of a metro extension in Stockholm, we demonstrate that congestion and crowding effects constitute more than a third of the total benefits and that a conventional static model underestimates these effects vastly. In another case study, we analyse various operational measures and find that the three main measures (boarding through all doors, headway-based holding and bus lanes) had an overall positive impact on service performance and that synergetic effects exist. For the congestion charging system in Gothenburg, we demonstrate that a hierarchal route choice model with a continuous value of time distribution gives realistic predictions of route choice effects although the assignment is static. We use the model to show that the net social benefit of the charging system in Gothenburg is positive, but that low income groups pay a larger share of their income than high income groups. To analyse congestion charges in Stockholm however, integration of dynamic traffic assignment with the demand model is necessary, and we demonstrate that this is fully possible. Models able to correctly predict these effects highlight the surprisingly large travel time savings of pricing policies and small operational measures. These measures are cheap compared to investments in new infrastructure and their implementation can therefore lead to large societal gains.

QC 20160829

No
Traffic congestion in communication networks can dramatically deteriorate user-perceived Quality-of-Service (QoS). The integration of the Random Early Detection (RED) and priority scheduling mechanisms is a promising scheme for congestion control and provisioning of differentiated QoS required by multimedia applications. Although analytical modelling of RED congestion control has received significant research efforts, the performance models reported in the current literature were primarily restricted to the RED algorithm only without consideration of traffic scheduling scheme for QoS differentiation. Moreover, for analytical tractability, these models were developed under the simplified assumption that the traffic follows Short-Range-Dependent (SRD) arrival processes (e.g., Poisson or Markov processes), which are unable to capture the self-similar nature (i.e., scale-invariant burstiness) of multimedia traffic in modern communication networks. To fill these gaps, this paper presents a new analytical model of RED congestion control for prioritized multi-class self-similar traffic. The closed-form expressions for the loss probability of individual traffic classes are derived. The effectiveness and accuracy of the model are validated through extensive comparison between analytical and simulation results. To illustrate its application, the model is adopted as a cost-effective tool to investigate the optimal threshold configuration and minimize the required buffer space with congestion control.

Access to the large web content hosted all over the world by users of the Internet engage many hosts, routers/switches and faster links. They challenge the internet backbone to operate at its capacity to assure e±cient content access. This may result in congestion and raises concerns over various Quality of Service (QoS) issues like high delays, high packet loss and low throughput of the system for various Internet applications. Thus, there is a need to develop effective congestion control mechanisms in order to meet various Quality of Service (QoS) related performance parameters. In this paper, our emphasis is on the Active Queue Management (AQM) mechanisms, particularly Random Early Detection (RED). We propose a threshold based novel analytical model based on standard RED mechanism. Various numerical examples are presented for Internet traffic scenarios containing both the burstiness and correlation properties of the network traffic.

Transmission pricing and congestion management are two important aspects of modern power sectors working under a deregulated environment or moving towards a deregulated system (open access) from a regulated environment. The transformation of power sector for open access environment with the participation of private sector and potential power suppliers under the regime of trading electricity as a commodity is aimed at overcoming some of the limitations faced by the vertically integrated system. It is believed that this transformation will bring in new technologies, efficient and alternative sources of power which are greener, self sustainable and competitive. There is ever increasing demand for electrical power due to the changing life style of human beings fueled by modernization and growth. Augmentation of existing capacity, siting of new power plants, and a search for alternate viable sources of energy that have lesser impact on environment are being taken up. With the integration of power plants into the grid depending upon the type, loca- tion and technology used, the cost of energy production also differs. In interconnected networks, power can flow from one point to other point in infinite number of possible paths which is decided by the circuit parameters, operating conditions, topology of network and the connected loads. The transmission facility provided for power transfer has to recover the charges from the entities present in the network based on the extent of utilization. Since power transmission losses account for nearly 4 to 8% of the total generation, this has to be accounted for and shared properly among the entities depending upon the connected generation/load. In this context, this thesis aims to evaluate the shortcomings of existing tracing methods and proposes a tracing method based upon the actual operating conditions of the network taking into account the network parameters, voltage gradient among the connected buses and topology of the network as obtained by the online state estimator/load flow studies. The concept proposed is relatively simple and easy to implement in a given transactional period. The proposed method is compared against one of the existing tracing technique available in literature. Both active and reactive power tracing is handled at one go. The summation of partial contributions from all the sources in any given line of the system always matches with that of the respective base case ow. The AC power flow equations themselves are nonlinear in nature. Since the sum of respective partial flows in a given branch is always equal to the original ow, these are termed as virtual flows and the effect of nonlinearity is still unknown. The virtual flows in a given line are complex in nature and their complex sum is equal to the original complex power flows as in the base case. It is required to determine whether these are the true partial flows. To answer this, a DC equivalent of the original AC network is proposed and is called as the R - P equivalent model. This model consists of only the resistances as that of original network (the resistances of transformers and lines neglecting the series reactance and the shunt charging) only. The real power injections in a AC network i.e. sources into respective buses and loads (negative real power injections) are taken as injection measurements of this R P model and the bus voltages (purely real quantities) are estimated using the method of least squares. Complex quantities are absent in this model and only real terms which are either sums or differences are present. For this model, virtual flows are evaluated and it has been verified that the virtual real power contributions from sources are in near agreement with the original AC network. This implies that the virtual flows determined for the original network can be applied for day-to-day applications. An important feature of the virtual flows is that it is possible to identify counter ow components. Counter flow components are the transactions taking place in opposite direction to the net flow in that branch. If a particular source is produces counter flow in a given line, then it is in effect reducing congestion to that extent. This information is lacking in most of the existing techniques. Counter flows are useful in managing congestion. HVDC links are integrated with HVAC systems in order to transfer bulk power and for the additional advantages they offer. The incremental cost of a DC link is zero due to the closed loop control techniques implemented to maintain constant power transfer (excluding constant voltage or constant current control). Consequently, cost allocation to HVDC is still a problem. The proposed virtual power flow tracing method is extended to HVAC systems integrated with HVDC in order to determine the extent of utilization of a given link by the sources. Before evaluating the virtual contributions to the HVDC links, the steady state operating condition of the combined system is obtained by per-forming a sequential load flow. Congestion is one of the main aspects of a deregulated system, and is a result of several transactions taking place simultaneously through a given transmission facility. If congestion is managed by providing pricing signals for the transmission usage by the parties involved. It can also be due to the non-availability of transmission paths due to line outages as a result of contingencies. In such a case, generation active power redispatch is considered as a viable option in addition to other available controls such as phase shifters and UPFCs to streamline the transactions within the available corridors. The virtual power flow tracing technique proposed in the thesis is used as a guiding factor for managing congestions occurring due to transactions/contingencies to the possible extent. The utilization of a given line by the sources present in the network in terms of real power flow is thus obtained. These line utilization factors are called as T-coefficients and these are approximately constant for moderate increments in active power change from the sources. A simple fuzzy logic based decision system is proposed in order to obtain active power rescheduling from the sources for managing network congestions. In order to enhance the system stability after rescheduling, reactive power optimization has life systems to illustrate the proposed approaches. For secure operation of the network, the ideal proportion of active power schedule from the sources present in the network for a given load pattern is found from network [FLG] matrix. The elements of this matrix are used in the computation of static voltage stability index (L-index). This [FLG] matrix is obtained from the partitioned network YBUS matrix and gives the Relative Electrical Distance (RED) of each of the loads with respect to the sources present in the network. From this RED, the ideal proportion of real power to be drawn by a given load from different sources can be determined. This proportion of active power scheduling from sources is termed as Desired Proportion of Generation (DPG). If the generations are scheduled accordingly, the network operates with less angular separation among system buses (improved angular stability), improved voltage profiles and better voltage stability. Further, the partitioned K[GL] matrix reveals information about the relative proportion in which the loads should draw active power from the sources as per DPG which is irrespective of the present scheduling. Other partitioned [Y ′ GG] matrix is useful in finding the deviation of the present active power output from the sources with respect to the ideal schedule. Many regional power systems are interconnected to form large integrated grids for both technical and economic benefits. In such situations, Generation Expansion Planning (GEP) has to be undertaken along with augmentation of existing transmission facilities. Generation expansion at certain locations need new transmission networks which involves serious problems such as getting right-of-way and environmental clearance. An approach to find suitable generation expansion locations in different zones with least requirements of transmission network expansion has been attempted using the concept of RED. For the anticipated load growth, the capacity and siting generation facilities are identified on zonal basis. Using sample systems and real life systems, the validity of the proposed approach is demonstrated using performance criteria such as voltage stability, effect on line MVA loadings and real power losses.