L'un des défis majeurs de l'évolution de l'architecture Internet est la définition d'une architecture protocolaire permettant d'améliorer le routage, et en particulier (i) conserver un système de routage gérable avec les technologies actuelles et futures c'est-à-dire, avec quelques millions d'états, (ii) offrir une architecture apte à faciliter la programmabilité du plan de transfert, (iii) proposer un système de routage évolutif pouvant être régulièrement optimisé avec uniquement les informations sur les flux actifs, (iv) fournir une séparation entre localisateurs et identificateurs pour la mobilité IP avancée, (v) faciliter un déploiement incrémental, (vi) mieux servir les services applicatifs "over-the-top". Le protocole LISP (\textit{Locator/Identifier Separation Protocol}) a été identifié comme l'un des protocoles émergents à cet égard. Dans son état actuel, il répond très bien aux besoins susmentionnés. Cependant, il subit des limitations lorsqu'il s'agit de prendre en compte la résilience et la capacité à réagir rapidement aux mises à jour de l'état du réseau. Ces inconvénients peuvent être compensés en améliorant l'architecture du plan de contrôle et ses algorithmes de routage. Dans cette thèse, nous proposons une nouvelle architecture réseau-système et expérimentons de nouvelles primitives de plan de contrôle, ainsi que d'algorithmes de diffusion des états, en testant son passage à l'échelle avec différentes conditions de réseau. Nous concevons et construisons d'abord un nœud de plan de données et de plan de contrôle LISP open source. Nous le comparons avec d'autres implémentations en montrant que notre implémentation atteint des performances adaptées aux vrais déploiements. Nous montrons comment notre implémentation a permis la mise en oeuvre d'une plateforme d'expérimentation à grande échelle, la plate-forme LISP-Lab, en opération aussi bien les fonctions de plan de transfert que les fonctions de plan de contrôle. En suite, nous proposons une nouvelle solution pour les migrations à chaud de machines virtuelles à travers des centres de données géographiquement répartis sur des réseaux IP étendus. Des tests dans un testbed réel connecté nativement à Internet montrent qu'avec notre approche, nous pouvons facilement atteindre des temps d'arrêt inférieurs à la seconde lors de la migration sur une grande échelle, même pour des clients très distants. En outre, nous avons étudié des protocoles d'optimisation de réseau multicouche, en particulier en relation avec le protocole MPTCP (Multipath Transport Control Protocol), auquel LISP peut offrir une diversité de chemins pour l’agrégation de bande passante, ainsi qu’une plus grande confidentialité et fiabilité des connexions. Bien que nous ne puissions bénéficier que de quelques nœuds de réseau superposés, nous avons pu évaluer expérimentalement nos propositions en montrant l'impact positif de notre solution, l'impact négatif des longs temps d'aller-rétour sur certains sous-flux MPTCP, et la forte corrélation entre le temps d'aller-retour différentiel et le débit. Enfin, nous avons travaillé sur une refonte du plan de contrôle de LISP afin d’améliorer son fonctionnement du à l'échelle d’Internet, en facilitant la coopération entre les systèmes de mapping LISP et en introduisant plus d'automatisation dans la procédure de fourniture de services de connectivité LISP. Nous croyons qu'une telle optimisation pourrait sensibiliser la communauté des fournisseurs de services, générant de nouvelles opportunités commerciales liées aux services de cartographie LISP et l'application de politiques d'ingénierie de trafic interdomaines avancées dans le but d'obtenir de meilleures garanties de qualité de service. / One of the major challenges in the evolution of the Internet architecture is the definition of a protocol architecture that allows to solve the following major issues in Internet routing and traffic forwarding capabilities, (i) keeping a routing state that is manageable with current and forthcoming computing infrastructure – i.e., with few millions of states, (ii) offering a scalable pull architecture in support of data-plane programmability, (iii) offering a scalable forwarding plane able to be regularly optimized with only active flows information, (iv) offering locator/identifier separation for advanced IP mobility, (v) is incrementally deployable, (vi) can enhance the support of over-the-top services. The Locator/Identifier Separation Protocol (LISP) has been identified as one of the rising protocols in this respect. In its current status, it supports the above mentioned requirements at a level that is acceptable for basic networking environments. However, it shows too limited capacities when it comes to take into consideration fault resiliency and capability to react fast to network state updates. These shortcomings can be compensated by enhancing the control-plane architecture, and the routing algorithms therein. In this dissertation, we propose new protocol features and experiment novel control-plane primitives, as well as hybrid distributed-centralized routing state dissemination algorithms, to scale with different network conditions. We first design and build own open source LISP data-plane and control plane node, comparing it with other implementations, showing how our implementation can scale for large networks and reach performances suitable for real deployments. We present how our implementation served to operate all network nodes (data-plane and control-plane nodes) of a large scale experimentation testbed, the LISP-Lab testbed. Then we propose a novel LISP-based solution for VM live migrations across geographically separated datacenters over wide area IP networks. Experimenting it at large scale, we show that with our approach we can easily reach sub-second downtimes upon Internet-wide migration, even for very distant clients. Moreover, we investigate cross-layer network optimization protocols, in particular in relation with the Multipath Transport Control Protocol (MPTCP) to which LISP can deliver path diversity in support of bandwidth increase, confidentiality support and connection reliability, also using LISP traffic engineering network overlays. Despite we could benefit from only few overlay network nodes, we could experimentally evaluate our proposals showing the positive impact by using our solution, the negative impact of long round-trip times on some MPTCP subflows, and the strong correlation between the differential round-trip time among subflows and the throughput performance. Finally, we worked on a framework to improve LISP operation at the Internet scale, by facilitating cooperation between LISP Mapping Systems and introducing more automation in the LISP connectivity service delivery procedure. We believe such optimization could raise awareness among the service providers’ community, yielding new business opportunities related to LISP mapping services and the enforcement of advanced inter-domain traffic engineering policies for the sake of better quality of service guarantees.

One of the most effective measures of congestion control on freeways has been ramp metering, where vehicle entry to the freeway is regulated by traffic signals (meters). Meters are run with calibrated influx rates to prevent highway saturation. However, recent observations of some metering sites in San Diego, CA indicate that metering, during peak hour demand, is helping freeway flow while sometimes creating considerable traffic back-ups on local streets, transferring congestion problems from the freeway to intersections. Metering problems stem largely from the difficulty of designing an integrated, dynamic metering scheme that responds not only to changing freeway conditions but also to fluctuating demand throughout the ramp network; a scheme whose objective is to maintain adequate freeway throughput as well as minimize disproportionate ramp delays and queue overspills onto surface streets. Simulation modeling is a versatile, convenient, relatively inexpensive and safe systems analysis tool for evaluating alternative strategies to achieve the above objective. The objective of this research was to establish a basic building block for a discrete system simulation model, ONRAMP, based on a stochastic, mesoscopic, queueing approach. ONRAMP is for modeling entrance ramp geometry, vehicular generation, platooning and arrivals, queueing activities, meters and metering rates. The architecture of ONRAMP's molecular unit is designed in a fashion so that it can be, with some model calibration, duplicated for a number of ramps and, if necessary, integrated into some other larger freeway network models. SLAM.II simulation language is used for computer implementation. ONRAMP has been developed and partly validated using data from eight ramps at Interstate-B in San Diego. From a systems perspective, simulation will be short-sided and problem analysis is incomplete unless the other non-technical metering problems are explored and considered. These problems include the impacts of signalizing entrance ramps on the vitality of adjacent intersections, land use and development, "fair" geographic distribution of meters and metering rates throughout the freeway corridor, public acceptance and enforcement, and the role and influence of organizations in charge of decision making in this regard. Therefore, an outline of a contextual systems approach for problem analysis is suggested. Benefits and problems of freeway control via ramp metering, both operational short-term and strategic long-term, are discussed in two dimensions: global (freeway) and local (intersection). The results of a pilot study which includes interviews with field experts and law enforcement officials and a small motorist survey are presented.

Indiana University-Purdue University Indianapolis (IUPUI) / With the increasing number of vehicles on the road and the amount of time people spend driving their vehicles, traffic control and management has become an important part within logistics. Effective traffic control would involve traffic signal control and control over vehicle movement. Since Petri nets are versatile enough to represent traffic signals and traffic flow, it has become an important tool in urban traffic control. Many traffic systems are modeled using hybrid Petri nets. Chapter 1 briefly talks about traffic management systems and previous related work in the area of traffic control. Chapter 2 is a basic background on various Petri nets used in the study. The section also uses examples to demonstrate the working of Petri nets. Chapter 3 introduces the need for optimization in various industry. And then, it discusses different steps involved in optimizing a process. Chapter 4 discusses the existing model of two one-way intersection. In an effort to understand the model better, simulations are also carried out. Then, drawbacks of the existing model are discussed. This paves way for a new, improved, and realistic version of two one-way intersection. Various optimization steps discussed in Chapter 3 is used to optimize traffic light of the improved model. And then, a comparison between existing model and improved model is carried out. Chapter 5 expands the study of traffic models by connecting two different one-way intersection through a road (thus making it a network). Optimization and simulation of the connected-intersection model is also carried out. Chapter 6 is the summary which will provide a brief overview about each chapter.

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

[pt] O crescente consumo de energia já se tornou uma preocupação mundial e atualmente mais de quarenta países estão envolvidos em pesquisas e programas para criar mecanismos para economizá-la. No presente trabalho é tratado o problema de Engenharia de Tráfego com base na energia (em inglês, energy-aware Traffic Engineering) aplicado ao backbone de uma rede IP que utiliza como protocolo de roteamento um SPF (Shortest Path First), como o OSPF (Open Shortest Path First), por exemplo. Na abordagem proposta são considerados os problemas de desligamento de nós (roteadores) e circuitos, para a economia de energia; e da garantia de um nível de máxima utilização dos circuitos, para assegurar os requisitos de QoS. Para a resolução do problema de otimização, em lugar de adotarem-se métodos heurísticos, propõe-se o tratamento direto por meio de decomposição de Benders, segmentando um problema complicado e de elevada carga computacional em vários menores cuja resolução é mais simples e cuja convergência é mais rápida. / [en] The growing energy consumption has already become a global concern and currently more than forty countries are involved in researches and programs in order to create mechanisms to save it. This work deals with the energy-aware Traffic Engineering problem applied to the backbone of an IP network in which the used routing protocol is a SPF (Shortest Path First) one, such as OSPF (Open Shortest Path First), for example. The proposed approach considers the problem of switching-off nodes (routers) and circuits, for energy saving; and it also considers the problem of ensuring a maximum utilization level by the circuits, towards to assure QoS requirements. In order to solve the optimization problem, rather than adopting heuristic methods, we propose the direct processing by means of Benders decomposition, crumbling a complicated and hard to solve problem into several smaller ones whose resolution is more simple and whose convergence is faster.

<p>   </p> <p>Historically, roadway performance measures have focused almost exclusively on vehicular movement. In most urban settings, pedestrian movements typically outnumber vehicular movements significantly. However,  historically there has been no way to collect such data at scale in a systematic manner. With the widespread introduction of cameras for monitoring vehicular flow, there is an opportunity to leverage this infrastructure to acquire insights into the patterns and trends of pedestrian activities at signalized intersections in an automated and systematic manner. Such data and performance measures are critical inputs for detailed analysis of pedestrian movements. Overall, addressing this issue is a vital component of transportation agencies that seek to develop equitable treatment of all transportation system users including vulnerable road users. This dissertation addresses the gap in the literature regarding detailed characterization of pedestrian movement patterns and trends. The dissertation leverages data from signalized intersection cameras to (1) quantify the required duration for the pedestrian walk-interval based on pedestrian volume and geometric features of the intersection, (2) carry out time series analysis to acquire insights on pedestrian demand patterns and the influential variables, and (3) build machine learning algorithms to accurately predict pedestrian volumes and tie it to signal timing, to enhance service for all roadway users.</p> <p>The first study provides quantitative guidance for walk time interval selection. This part reports on 1,500 pedestrian movement observations from 12 signalized intersections with varying pedestrian demand, pedestrian storage areas, and pedestrian push-button locations. That data were used to develop a model predicting start-up time with an R2 of 0.89. The study concludes by presenting a quantitative table with four timing categories ranging from negligible volume to high volume and corresponding appropriate durations for the pedestrian walk interval time, based on the demand per cycle, storage area for pedestrians, and offset of the pedestrian push-button from the crosswalk.</p> <p>The second study describes several scalable techniques for measuring and analyzing the movement of pedestrians on a typical university campus. Approximately 35.6 million pedestrian movements over 19 months were tabulated in 15-minute counts of pedestrian volumes by intersection. Counts are used in evaluating pedestrian activity dependency on select explanatory variables at both the network and intersection levels at each time step for the entire analysis period. The study reports on time series correlation and cross-correlation and measures the time-dependency between pedestrian activities and influential factors such as the academic calendar, football games, basketball games, and graduation ceremonies. It provides a comprehensive understanding of the factors that are most influential of  pedestrian volumes at intersections.</p> <p>The third study presents a data-driven approach to predict pedestrian volume per intersection quadrant at 15-minute intervals, and to connect this information to signal timing. Machine learning random forest and XGBoost classification models were trained on a large dataset of pedestrian counts consisting of approximately 2.6 million observations collected through 19 months at 13 exclusive pedestrian service intersections. The predicted pedestrian volumes were then categorized per the pedestrian walk-interval categories to provide optimal signal timing for each intersection quadrant, thus enabling potential dynamic pedestrian signal timing at exclusive service intersections. The results of this study showed that the developed models accurately predict pedestrian volumes per 15-minute intervals for each quadrant of an intersection, with a high degree of precision and a prediction accuracy of 82.3%. Signal timing optimization based on predicted pedestrian volume can significantly improve pedestrian mobility and maximize traffic flow. </p> <p>The findings of this study provide valuable insights for traffic engineers and planners interested in developing and deploying dynamic pedestrian signal timing systems. It is a practical and effective solution for improving mobility for all roadway users at intersections with exclusive pedestrian service.</p> <p>  </p>

Augmented reality "AR" is a promising paradigm that can provide users with real-time, high-quality visualization of a wide variety of information. In AR, virtual objects are added to the real-world view in a real time. Using the AR technology can offer a very realistic environment for driving enhancement as well as driving performance testing under different scenarios. This can be achieved by adding virtual objects (people, vehicles, hazards, and other objects) to the normal view while driving in a safe controlled environment. In this dissertation, the feasibility of adapting the AR technology into traffic engineering was investigated. Two AR systems; AR Vehicle "ARV" system and Offline AR Simulator "OARSim" system were built. The systems' outcomes as well as the on-the-road driving under the AR were evaluated. In evaluating systems' outcomes, systems were successfully able to duplicate real scenes and generate new scenes without any visual inconsistency. In evaluating on-the-road driving under the AR, drivers' distance judgment, speed judgment, and level of comfort while driving were evaluated. In addition, our systems were used to conduct two traffic engineering studies; left-turn maneuver at un-signalized intersection, and horizontal visibility blockage when following a light truck vehicle. The results from this work supported the validity of our AR systems to be used as a surrogate to the field-testing for transportation research.

Traffic polarization in networks refers to the phenomenon where traffic tends to concentrate along specific routes or edges when doing multipath routing, leading to imbalanced flow patterns. This spatial distribution of traffic can result in congested and overburdened links, while other routes remain underutilized. Such imbalanced traffic distribution can lead to network bottlenecks, reduced throughput, and compromised Quality of Service for critical applications. These issues emphasize the urgent necessity to address traffic polarization and its detrimental impact on network efficiency and resilience. In this master thesis, we introduce a novel approach to tackle the problem of hash polarization and evaluate the performance of our implementation. Perhaps influenced by the RFC 2992 document, previous works always use the whole value of the hash result to do the multipath routing decisions, and therefore try to mitigate the polarization problem by developing more functions or reusing them. However, we investigate if the polarizion issue can be solved by utilizing different parts of the hash result. In this case, the most critical problem would be how to choose the bits of the hash result for the multipath routing decisions. Unfortunately, during the experiment, we discovered that the optimal performance design is influenced by many factors in the network topology and traffic demand pattern, making it difficult to summarize a universal law. Nevertheless, our research has proposed a mechanism called “bit-awareness”, which can significantly alleviate the problem of selecting overlapping bits, and hence addresses the polarization issue. / Trafikpolarisering i nätverk hänvisar till fenomenet där trafik tenderar att koncentreras längs specifika rutter eller kanter när man gör flervägsdirigering, vilket leder till obalanserade flödesmönster. Denna rumsliga fördelning av trafik kan resultera i överbelastade och överbelastade länkar, medan andra vägar förblir underutnyttjade. Sådan obalanserad trafikdistribution kan leda till nätverksflaskhalsar, minskad genomströmning och försämrad tjänstekvalitet för kritiska applikationer. Dessa frågor betonar det akuta behovet av att ta itu med trafikpolarisering och dess skadliga inverkan på nätverkseffektivitet och motståndskraft. I denna masteruppsats introducerar vi ett nytt tillvägagångssätt för att tackla problemet med hashpolarisering och utvärdera prestandan för vår implementering. Kanske påverkat av RFC 2992-dokumentet, skulle tidigare arbeten använda hela värdet av hashresultatet för att fatta beslut om flervägsdirigering och därför försöka mildra polariseringsproblemet genom att utveckla fler funktioner eller återanvända dem. Vi undrar dock om problemet kan lösas genom att använda olika delar av hashresultatet. I det här fallet skulle det mest avgörande problemet vara hur man väljer bitarna i hashresultatet för besluten om flervägsdirigering. Tyvärr upptäckte vi under experimentet att den optimala prestandadesignen påverkas av många faktorer i nätverkstopologin och trafikefterfrågan, vilket gör det svårt att sammanfatta en universell lag. Ändå har vår forskning föreslagit en mekanism som kallas ”bit-medvetenhet”, som avsevärt kan lindra problemet med att välja överlappande bitar, och därmed adresserar polariseringsfrågan.

As the United States continues to build and repair the ageing highway infrastructure, the bearing of freeway work zones will continue to impact the capacity. To predict the capacity of a freeway work zone, there are several tools available for engineers to evaluate these work zones but only microsimulation has the ability to simulate the driver behavior. One of the limitations of current car-following models is that they only account for one overall behavioral condition. This dissertation hypothesizes that drivers change their driving behavior as they drive through a freeway work zone compared to normal freeway conditions which has the potential to impact traffic operations and capacity of work zones. Psycho-physical car-following models are widely used in practice for simulating car-following. However, current simulation models may not fully capture car-following driver behavior specific to freeway work zones. This dissertation presents a new multidimensional psycho-physical framework for modeling car-following based on statistical evaluation of work zone and non-work zone driver behavior. This new framework is close in character to the Wiedemann model used in popular traffic simulation software such as VISSIM. This dissertation used two methodologies for collecting data: (1) a questionnaire to collect demographics and work zone behavior data and (2) a real-time vehicle data from a field experiment involving human participants. It is hypothesized that the parameters needed to calibrate the multidimensional framework for work zone driver behavior can be derived statistically by using data collected from runs of an Instrumented Research Vehicle (IRV) in a Living Laboratory (LL) along a roadway. The design of this LL included the development of an Instrumented Research Vehicle (IRV) to capture the natural car-following response of a driver when entering and passing through a freeway work zone. The development of a Connected Mobile Traffic Sensing (CMTS) system, which included state-of-the-art ITS technologies, supports the LL environment by providing the connectivity, interoperability and data processing of the natural, real-life setting. The IRV and CMTS system are tools designed to support the concept of a LL which facilitates the experimental environment to capture and calibrate natural driver behavior. The objective is to have these participants drive the instrumented vehicle and collect the relative distance and the relative velocity between the instrumented vehicle and the vehicle in the front of the instrumented vehicle. A Phase I pilot test was conducted with 10 participants to evaluate the experiment and make any adjustments prior to the full Phase II driver test. The Phase II driver test recruited a group of 64 participants to drive the IRV through an LL set up along a work zone on I-95 near Washington D.C. in order to validate this hypothesis In this dissertation, a new framework was applied and it demonstrated that there are four different categories of car-following behavior models each with different parameter distributions. The four categories are divided by traffic condition (congested vs. uncongested) and by roadway condition (work zone vs. non-work zone). The calibrated threshold values are presented for each of these four categories. By applying this new multidimensional framework, modeling of car-following behavior can enhance vehicle behavior in microsimulation modeling. This dissertation also explored driver behavior through combining vehicle data and survey techniques to augment the model calibrations to improve the understanding of car-following behavior in freeway work zones. The results identify a set of survey questions that can potentially guide the selection of parameters for car-fallowing models. The findings presented in this dissertation can be used to improve the performance of driver behavior models specific to work zones. This in return will more acutely forecast the impact a work zone design has on capacity during congestion.

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