Ho Chi-Fong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 63-[64]). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- The 2.5G Systems --- p.3 / Chapter 1.2.1 --- HSCSD --- p.3 / Chapter 1.2.2 --- GPRS --- p.3 / Chapter 1.2.3 --- EDGE --- p.4 / Chapter 1.2.4 --- IS-136 --- p.4 / Chapter 1.3 --- The Evolution from 2G/2.5G to 3G --- p.4 / Chapter 1.3.1 --- GSM Data Evolution --- p.4 / Chapter 1.3.2 --- TDMA Data Evolution --- p.5 / Chapter 1.3.3 --- CDMA Data Evolution --- p.6 / Chapter 1.4 --- UTRA --- p.7 / Chapter 1.4.1 --- UTRA FDD --- p.8 / Chapter 1.4.2 --- UTRA TDD --- p.18 / Chapter 1.4.3 --- Transport Channels --- p.25 / Chapter 2 --- Spreading Factor Optimization for FDD Downlink --- p.27 / Chapter 2.1 --- The Optimal Channel Splitting Problem --- p.28 / Chapter 2.2 --- Spreading Factor Optimization for FDD Downlink Dedicated Chan- nel --- p.30 / Chapter 3 --- Random Access Channel Stability Control --- p.33 / Chapter 3.1 --- Random Access Slotted Aloha --- p.33 / Chapter 3.1.1 --- System model --- p.33 / Chapter 3.1.2 --- Probability of Code-Collision --- p.34 / Chapter 3.1.3 --- Throughput Analysis of Random Access in TD/CDMA System --- p.37 / Chapter 3.1.4 --- Retransmission --- p.42 / Chapter 3.1.5 --- System Delay --- p.42 / Chapter 3.2 --- Random Access Channel Stability Control --- p.43 / Chapter 3.2.1 --- System Model --- p.43 / Chapter 3.2.2 --- Random Access Procedure --- p.44 / Chapter 3.3 --- Random Access Channel Stability Control Alogrithm --- p.47 / Chapter 3.3.1 --- Simulation --- p.49 / Chapter 3.4 --- Multi-class Model --- p.55 / Chapter 4 --- Conclusions and Topics for Future Study --- p.60 / Chapter 4.1 --- Thesis Conclusions --- p.60 / Chapter 4.2 --- Future Work --- p.61 / Chapter 4.2.1 --- Downlink and Uplink resource allocation in TDD --- p.61 / Chapter 4.2.2 --- Resource Unit Packing in TDD --- p.62 / Chapter 4.2.3 --- Other Topics --- p.62 / Bibliography --- p.63

Nos últimos anos, os países desenvolvidos vêm dedicando crescentes esforços para integrar o Veículo Aéreo Não Tripulado (VANT) no espaço aéreo controlado, visando sua utilização para fins civis. Embora este tema ainda não tenha consenso quanto aos critérios a serem adotados, é de comum acordo na comunidade que, no mínimo, devam ser mantidos os atuais níveis de segurança (\"Safety\") praticados pela aviação civil mundial. Neste cenário, a convivência entre aeronaves comerciais, com cada vez mais passageiros e aeronaves não tripuladas, traz sérias preocupações com relação à capacidade que o sistema atual de navegação, controle, vigilância e de Gerenciamento de Tráfego Aéreo tem para lidar com situações de perigo decorrentes da aproximação entre estas duas categorias de aeronaves. Neste contexto, esta tese propõe uma modelagem de um VANT, tendo-se como ponto de partida os conceitos de robô móvel, cujo modelo de inteligência é fundamentado em Inteligência Artificial Distribuída (IAD), implementável segundo o paradigma de Sistemas Multi-Agentes (SMA) e que leve em consideração os principais requisitos de \"Safety\" exigidos pelo \"Communication Navigation System/Air Traffic Management\" (CNS/ATM), de modo a permitir a futura inserção destas aeronaves no espaço aéreo controlado. / During the last years, developed countries are conducting efforts to integrate Unmanned Aircraft Vehicles (UAVs) to the controlled airspace, aiming at their civilian use. So far, there has been no common consensus on the criteria to be adopted by the community that should, at least, keep the minimum safety levels international aviation has already attained. In this scenario, commercial aircrafts - with more and more passengers - and UAVs will share the same space. There will be a lot of concern related to the actual navigation, control and surveillance system capacity as well as to the air traffic control management ability to handle potentially dangerous situations due to the approximation between aircrafts of these two categories. Based on this scenario, this thesis proposes an UAV modeling having as starting point the mobile robot concept, of which the intelligence model based on Distributed Artificial Intelligence, can be implemented by using the Multi Agent Systems paradigm. This paradigm should take the main safety requirements as an obligation, as defined by the Communication Navigation System/Air Traffic Management (CNS/ATM), as a way of handling the future insertion of UAVs into the controlled airspace.

Neste trabalho é avaliado o desempenho operacional de uma nova configuração idealizada para a operação de rotatórias de três pernas (prioridade para os veículos da via principal com semáforos próximos). Nesta avaliação é comparado o novo sistema de operação com outros dois usualmente empregados: (1) prioridade para os veículos que estão circulando na ilha central (rotatória convencional) e (2) prioridade para os veículos da via principal sem o emprego de semáforo, bem como, com base nos resultados das comparações realizadas, são estabelecidas as condições dos fluxos de tráfego em que é indicada uma ou outra configuração. Os valores obtidos nas simulações mostram, de forma inequívoca, o desempenho operacional superior da rotatória com prioridade para a via principal com semáforos próximos, adequadamente programados, no caso de fluxos altos. O emprego de semáforos próximos reduz significativamente o atraso na aproximação crítica e, em consequência, o tamanho da fila, como consequência do aumento expressivo da capacidade de tráfego da rotatória. Os resultados da simulação corroboram o que se pode observar nos sistemas implantados na cidade de Araraquara, onde a colocação de semáforos próximos de rotatórias de três pernas melhorou de forma significativa o desempenho operacional dos dispositivos, reduzindo o atraso crítico e o tamanho da fila crítica e aumentando a capacidade. O acompanhamento da acidentalidade nas rotatórias onde foram colocados semáforos próximos na cidade de Araraquara mostra uma redução dos acidentes graves de aproximadamente 90%. Uma explicação para essa redução pode ser devido ao aumento da paciência dos motoristas em esperar uma brecha maior para entrar na rotatória, pois sabem que, esporadicamente, há uma interrupção do fluxo na via principal. / In this study the operational performance is measured of a new idealized configuration for the operation in three-legged traffic circles (priority way for the vehicles from the main street with traffic lights nearby). This measured is compared the new operational system with two others usually systems: (1) priority for the circulating traffic (conventional roundabout) and (2) priority for vehicles from the main street without traffic lights. Also, based on the results from the comparisons, seek to establish what traffic flow conditions are better for a given configuration. The values obtained from the simulations demonstrate, clearly, the superior operational performance of the traffic circle with main road priority combined with properly programmed traffic lights nearby, in the case of high flows. The use of traffic lights reduces significantly the delay from the critical approach, and consequently, the queue length, as a consequence resulting on significant traffic capacity increase at the intersection. Simulation results validate what can be seen in Araraquara, where the installation of traffic lights near from the three-legged traffic circle improved significantly the operating performance of the devices, reducing the critical delay and critical queue size and increasing the effective capacity. Monitoring the accident rate in traffic circles where traffic lights nearby were placed in Araraquara shows a reduction of approximately 90% in serious accidents. An explanation of this reduction may be due to the increased of patience of drivers in wait for a larger gap to enter on the roundabout, because they know there will be an interruption on the main street, sporadically.

Neste trabalho é avaliado o desempenho operacional de uma nova configuração idealizada para a operação de rotatórias de três pernas (prioridade para os veículos da via principal com semáforos próximos). Nesta avaliação é comparado o novo sistema de operação com outros dois usualmente empregados: (1) prioridade para os veículos que estão circulando na ilha central (rotatória convencional) e (2) prioridade para os veículos da via principal sem o emprego de semáforo, bem como, com base nos resultados das comparações realizadas, são estabelecidas as condições dos fluxos de tráfego em que é indicada uma ou outra configuração. Os valores obtidos nas simulações mostram, de forma inequívoca, o desempenho operacional superior da rotatória com prioridade para a via principal com semáforos próximos, adequadamente programados, no caso de fluxos altos. O emprego de semáforos próximos reduz significativamente o atraso na aproximação crítica e, em consequência, o tamanho da fila, como consequência do aumento expressivo da capacidade de tráfego da rotatória. Os resultados da simulação corroboram o que se pode observar nos sistemas implantados na cidade de Araraquara, onde a colocação de semáforos próximos de rotatórias de três pernas melhorou de forma significativa o desempenho operacional dos dispositivos, reduzindo o atraso crítico e o tamanho da fila crítica e aumentando a capacidade. O acompanhamento da acidentalidade nas rotatórias onde foram colocados semáforos próximos na cidade de Araraquara mostra uma redução dos acidentes graves de aproximadamente 90%. Uma explicação para essa redução pode ser devido ao aumento da paciência dos motoristas em esperar uma brecha maior para entrar na rotatória, pois sabem que, esporadicamente, há uma interrupção do fluxo na via principal. / In this study the operational performance is measured of a new idealized configuration for the operation in three-legged traffic circles (priority way for the vehicles from the main street with traffic lights nearby). This measured is compared the new operational system with two others usually systems: (1) priority for the circulating traffic (conventional roundabout) and (2) priority for vehicles from the main street without traffic lights. Also, based on the results from the comparisons, seek to establish what traffic flow conditions are better for a given configuration. The values obtained from the simulations demonstrate, clearly, the superior operational performance of the traffic circle with main road priority combined with properly programmed traffic lights nearby, in the case of high flows. The use of traffic lights reduces significantly the delay from the critical approach, and consequently, the queue length, as a consequence resulting on significant traffic capacity increase at the intersection. Simulation results validate what can be seen in Araraquara, where the installation of traffic lights near from the three-legged traffic circle improved significantly the operating performance of the devices, reducing the critical delay and critical queue size and increasing the effective capacity. Monitoring the accident rate in traffic circles where traffic lights nearby were placed in Araraquara shows a reduction of approximately 90% in serious accidents. An explanation of this reduction may be due to the increased of patience of drivers in wait for a larger gap to enter on the roundabout, because they know there will be an interruption on the main street, sporadically.

Dans le cadre de cette thèse, nous nous intéressons à la coordination et l'optimisation du trafic aux intersections des réseaux routiers, avec la particularité de considérer des véhicules autonomes intelligents. Cette thèse est organisée en deux grandes parties. La première se concentre sur le problème du partage d'un espace de voie par deux files de véhicules évoluant en sens opposés. L'état de l'art montre le peu de travaux abordant cette question. Nous explorons deux approches par coordination réactive, en relation avec un critère de minimisation des retards. Les performances de ces approches ont été mesurées statistiquement en simulation. La deuxième partie de la thèse s'attaque au problème générique de la gestion du trafic au sein d'un réseau routier. Nous développons une approche originale à deux égards: d'une part elle explore un principe de passage en alternance des flux permettant de ne pas arrêter les véhicules aux intersections, et d'autre part, elle propose des algorithmes d'optimisationdistribuée de ce passage alterné au niveau de chaque intersection et au niveau du réseau global. La thèse présente successivement les choix de modélisation, les algorithmes et l'étude en simulation de leurs performances comparées à desapproches existantes / In this thesis, we focus on traffic coordination and optimization in road intersections, while accounting for intelligent autonomous vehicles. This thesis is organized in two parts. The first part focuses on the problem of sharing a one-lane road between two opposite flows of vehicles. The state of the art shows few studies addressing this issue. We propose two reactive coordination approaches that minimize vehicle delays and measure their performances statistically through simulations. The second part of the thesis addresses the problem of generic traffic management in a traffic network. We develop a stop-free approach that explores a principle alternating vehicles between flows at intersections, and it provides distributed algorithms optimizing this alternation at each intersection and in the overall network. We present the modeling choices, the algorithms and the simulation study of our approach and we compare its performances with existing approaches

Present day air traffc control is reaching its operational limits and accommodating future traffic growth will be a challenging task for air traffic service providers and airline operators. Free Flight is a proposed transition from a highly-structured and centrally-controlled air traffic system to a self-optimized and highly-distributed system. In Free Flight, pilots will have the flexibility of real-time trajectory planning and dynamic route optimization given airspace constraints (traffic, weather etc.). A variety of advanced air traffc management (ATM) concepts are proposed as enabling technologies for the realization of Free Flight. Since these concepts can be exposed to unforeseen and challenging scenarios in Free Flight, they need to be validated and evaluated in order to implement the most effective systems in the field. Evaluation of advanced ATM concepts is a challenging task due to the limitations in the existing scenario generation methodologies and limited availability of a common platform (air traffic simulator) where diverse ATM concepts can be modeled and evaluated. Their rigorous evaluation on safety metrics, in a variety of complex scenarios, can provide an insight into their performance, which can help improve upon them while developing new ones. In this thesis, I propose a non-propriety, non-commercial air traffic simulation system, with a novel representation of airspace, which can prototype advanced ATM concepts such as conflict detection and resolution, airborne weather avoidance and cockpit display of traffic information. I then propose a novel evolutionary computation methodology to algorithmically generate a massive number of conflict scenarios of increasing complexity in order to evaluate conflict detection algorithms. I illustrate the methodology in detail by quantitative evaluation of three conflict detection algorithms, from the literature, on safety metrics. I then propose the use of data mining techniques for the discovery of interesting relationships, that may exist implicitly, in the algorithm's performance data. The data mining techniques formulate the conflict characteristics, which may lead to algorithm failure, using if-then rules. Using the rule sets for each algorithm, I propose an ensemble of conflict detection algorithms which uses a switch mechanism to direct the subsequent conflict probes to an algorithm which is less vulnerable to failure in a given conflict scenario. The objective is to form a predictive model for algorithm's vulnerability which can then be included in an ensemble that can minimize the overall vulnerability of the system. In summary, the contributions of this thesis are: 1. A non-propriety, non-commercial air traffic simulation system with a novel representation of airspace for efficient modeling of advanced ATM concepts. 2. An Ant-based dynamic weather avoidance algorithm for traffic-constrained enroute airspace. 3. A novel representation of 4D air traffic scenario that allows the use of an evolutionary computation methodology to evolve complex conflict scenarios for the evaluation of conflict detection algorithms. 4. An evaluation framework where scenario generation, scenario evaluation and scenario evolution processes can be carried out in an integrated manner for rigorous evaluation of advanced ATM concepts. 5. A methodology for forming an intelligent ensemble of conflict detection algorithms by data mining the scenario space.

The numerous man-made disasters and natural catastrophes that menace major communities accentuate the need for proper planning for emergency evacuation. Transportation networks in cities evolve over long time spans in tandem with population growth and evolution of travel patterns. In emergencies, travel demand and travel patterns drastically change from the usual everyday volumes and patterns. Given that most US and Canadian cities are already congested and operating near capacity during peak periods, network performance can severely deteriorate if drastic changes in Origin-Destination (O-D) demand patterns occur during or after a disaster. Also, loss of capacity due to the disaster and associated incidents can further complicate the matter. Therefore, the primary goal when a disaster or hazardous event occurs is to coordinate, control, and possibly optimize the utilization of the existing transportation network capacity. Emergency operation management centres face multi-faceted challenges in anticipating evacuation flows and providing proactive actions to guide and coordinate the public towards safe shelters. Numerous studies have contributed to developing and testing strategies that have the potential to mitigate the consequences of emergency situations. They primarily investigate the effect of some proposed strategies that have the potential of improving the performance of the evacuation process with modelling and optimization techniques. However, most of these studies are inherently restricted to evacuating automobile traffic using a certain strategy without considering other modes of transportation. Moreover, little emphasis is given to studying the interaction between the various strategies that could be potentially synergized to expedite the evacuation process. Also, the absence of an accurate representation of the spatial and temporal distribution of the population and the failure to identify the available modes and populations that are captive to certain modes contribute to the absence of multimodal evacuation procedures. Incorporating multiple modes into emergency evacuation has the potential to expedite the evacuation process and is essential to assuring the effective evacuation of transit-captive and special-needs populations . This dissertation presents a novel multimodal optimization framework that combines vehicular traffic and mass transit for emergency evacuation. A multi-objective approach is used to optimize the multimodal evacuation problem. For automobile evacuees, an Optimal Spatio-Temporal Evacuation (OSTE) framework is presented for generating optimal demand scheduling, destination choices and route choices, simultaneously. OSTE implements Dynamic Traffic Assignment (DTA) techniques coupled with parallel distributed genetic optimization to guarantee a near global optimal solution. For transit evacuees, a Multi-Depots, Time Constrained, Pick-up and Delivery Vehicle Routing Problem (MDTCPD-VRP) framework is presented to model the use of public transit vehicles in evacuation situations. The MDTCPD-VRP implements constraint programming and local search techniques to optimize certain objective functions and satisfy a set of constraints. The OSTE and MDTCPD-VRP platforms are integrated into one framework to replicate the impact of congestion caused by traffic on transit vehicle travel times. A proof-of-concept prototype has been tested; it investigates the optimization of a multimodal evacuation of a portion of the Toronto Waterfront area. It also assesses the impact of multiple objective functions on emergency evacuation while attempting to achieve an equilibrium state between transit modes and vehicular traffic. Then, a large-scale application, including a demand estimation model from a regional travel survey, is conducted for the evacuation of the entire City of Toronto. This framework addresses many limitations of existing evacuation planning models by: 1) synergizing multiple evacuation strategies; 2) utilizing robust optimization and solution algorithms that can tackle such multi-dimensional non deterministic problem; 3) estimating the spatial and temporal distribution of evacuation demand; 4) identifying the transit-dependent population; 5) integrating multiple modes in emergency evacuation. The framework presents a significant step forward in emergency evacuation optimization.

The numerous man-made disasters and natural catastrophes that menace major communities accentuate the need for proper planning for emergency evacuation. Transportation networks in cities evolve over long time spans in tandem with population growth and evolution of travel patterns. In emergencies, travel demand and travel patterns drastically change from the usual everyday volumes and patterns. Given that most US and Canadian cities are already congested and operating near capacity during peak periods, network performance can severely deteriorate if drastic changes in Origin-Destination (O-D) demand patterns occur during or after a disaster. Also, loss of capacity due to the disaster and associated incidents can further complicate the matter. Therefore, the primary goal when a disaster or hazardous event occurs is to coordinate, control, and possibly optimize the utilization of the existing transportation network capacity. Emergency operation management centres face multi-faceted challenges in anticipating evacuation flows and providing proactive actions to guide and coordinate the public towards safe shelters. Numerous studies have contributed to developing and testing strategies that have the potential to mitigate the consequences of emergency situations. They primarily investigate the effect of some proposed strategies that have the potential of improving the performance of the evacuation process with modelling and optimization techniques. However, most of these studies are inherently restricted to evacuating automobile traffic using a certain strategy without considering other modes of transportation. Moreover, little emphasis is given to studying the interaction between the various strategies that could be potentially synergized to expedite the evacuation process. Also, the absence of an accurate representation of the spatial and temporal distribution of the population and the failure to identify the available modes and populations that are captive to certain modes contribute to the absence of multimodal evacuation procedures. Incorporating multiple modes into emergency evacuation has the potential to expedite the evacuation process and is essential to assuring the effective evacuation of transit-captive and special-needs populations . This dissertation presents a novel multimodal optimization framework that combines vehicular traffic and mass transit for emergency evacuation. A multi-objective approach is used to optimize the multimodal evacuation problem. For automobile evacuees, an Optimal Spatio-Temporal Evacuation (OSTE) framework is presented for generating optimal demand scheduling, destination choices and route choices, simultaneously. OSTE implements Dynamic Traffic Assignment (DTA) techniques coupled with parallel distributed genetic optimization to guarantee a near global optimal solution. For transit evacuees, a Multi-Depots, Time Constrained, Pick-up and Delivery Vehicle Routing Problem (MDTCPD-VRP) framework is presented to model the use of public transit vehicles in evacuation situations. The MDTCPD-VRP implements constraint programming and local search techniques to optimize certain objective functions and satisfy a set of constraints. The OSTE and MDTCPD-VRP platforms are integrated into one framework to replicate the impact of congestion caused by traffic on transit vehicle travel times. A proof-of-concept prototype has been tested; it investigates the optimization of a multimodal evacuation of a portion of the Toronto Waterfront area. It also assesses the impact of multiple objective functions on emergency evacuation while attempting to achieve an equilibrium state between transit modes and vehicular traffic. Then, a large-scale application, including a demand estimation model from a regional travel survey, is conducted for the evacuation of the entire City of Toronto. This framework addresses many limitations of existing evacuation planning models by: 1) synergizing multiple evacuation strategies; 2) utilizing robust optimization and solution algorithms that can tackle such multi-dimensional non deterministic problem; 3) estimating the spatial and temporal distribution of evacuation demand; 4) identifying the transit-dependent population; 5) integrating multiple modes in emergency evacuation. The framework presents a significant step forward in emergency evacuation optimization.

Video image detection system (VDS) equipment provides real-time traffic data for monitored highways directly to the traffic management center (TMC) of the Georgia Department of Transportation. However, at any given time, approximately 30 to 35% of the 1,600 camera stations (STNs) fail to work properly. The main reasons for malfunctions in the VDS system include long term road construction activity and operational limitations. Thus, providing alternative data sources for offline VDS stations and developing tools that can help detect problems with VDS stations can facilitate the successful operation of the TMC. To estimate the travel speed of non-working STNs, this research examined global positioning system (GPS) data from vehicles using the ATMS-monitored freeway system as a potential alternative measure to VDS. The goal of this study is to compare VDS speed data for the estimation of the travel speed on freeways with GPS-equipped vehicle trip data, and to assess the differences between these measurements as a potential function of traffic and roadway conditions, environmental, conditions, and driver/vehicle characteristics. The difference between GPS and VDS speeds is affected by various factors such as congestion level (expressed as level of service), onroad truck percentage, facility design (number of lanes and freeway sub-type), posted speed limit, weather, daylight, and time of day. The relationship between monitored speed difference and congestion level was particularly large and was observed to interact with most other factors. Classification and regression tree (CART) analysis results indicated that driver age was the most relevant variable in explaining variation for the southbound of freeway dataset and freeway sub-type, speed limit, driver age, and number of lane were the most influential variables for the northbound of freeway dataset. The combination of several variables had significant contribution in the reduction of the deviation for both the northbound and the southbound dataset. Although this study identifies potential relationships between speed difference and various factors, the results of the CART analysis should be considered with the driver sample size to yield statistically significant results. Expanded sampling with larger number of drivers would enrich this study results.

Quality of service is commonly used to shape network traffic to meet specified criteria. The various scenarios include limiting and reserving bandwidth for a particular application, host or user, prioritizing latency sensitive traffic or equal distribution of unreserved bandwidth. The DynShaper software distributes and controls a traffic quota by more sophisticated means than fixed per user limits and simple disconnection after the user reaches the limit. It distributes the quota on a daily basis, where each day receives the same share. The users are sorted into predefined groups with different bandwidths depending on their recent consumption. This classification is periodically updated to ensure the sorting order is maintained. The bandwidths of these groups is dynamically adjusted depending on the actual consumption to provide an efficient utilization. This thesis presents another distribution model using a case-based reasoning approach, a method for machine learning which is classified as conventional artificial intelligence. Case-based reasoning tries to solve new problems based on the solutions of similar problems from the past. Controlling the network traffic to remain within a fixed quota can be modeled as such a problem if the traffic patterns are recurring. Possible solutions can be derived from statistical data and altered to suit the new problems. When an untested solution is applied, the software supervises the execution and revises the solution accordingly, if the actual results deviate from the precalculated schedule.