Traffic Engineering

In this paper we study the Multimodal Network Design Problem (MNDP); this problem arises when a decision maker (e.g. traffic authority) can operate on different transportation modes simultaneously. For this problem we formulate a general multimodal network design model from which descend multimodal and monomodal network design submodels. Possible solution approaches and research perspectives are identified. This paper, therefore, provides a general framework on multimodal and monomodal network design problems and their modeling.

Keywords: Multimodal approach, network design problem, elastic demand.

There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, cen-timeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.

Adaptive traffic control systems (ATCS) continuously adapt to changing traffic in order to improve traffic performance at signalized intersections. Typical before-after studies evaluate the success of ATCS deployments by assessing only the postimplementation traffic performance. Fully assessing the feasibility of ATCS implementation, however, requires evaluating the changes in long-term ATCS performance with changing traffic demands. This paper illustrates the assessment of long-term ATCS performance of two study corridors. The study uses volume=capacity (v=c) ratio to evaluate the effects of changing corridor flow on corridor-wide delay benefits. The results show that the Sydney Coordinated Adaptive Traffic System (SCATS) improves corridor flow and decreases corridor-wide delays up to a point of ineffectiveness, beyond which the ATCS performance begins to decrease. The ineffectiveness point helps in deriving a reasonable estimate for the magnitude and duration of potential ATCS deployment benefits.

The primary objectives of this study are to develop two roundabout entry capacity models using a regression-based multiple non-linear regression model (MNLR) and artificial intelligence (AI)-based ANFIS (adaptive neuro-fuzzy inference system) model under heterogeneous traffic conditions. ANFIS is the latest technique in the field of AI that integrates both neural networks and fuzzy logic principles in a single framework. Required data have been collected from 27 roundabouts in eight states of India. To assess the significance of these models and select the best model among them, modified rank index is applied in this study. The coefficient of determination (R 2) and Nash-Sutcliffe model efficiency coefficient 'E' values are found to be 0.92, 0.91 and 0.98, 0.98 for the MNLR and ANFIS model, respectively. The ANFIS model is found to be the best model in this study. However, from a practical point of view, the MNLR model is recommended for determining roundabout entry capacity under heterogeneous traffic conditions. Sensitivity analysis reports that critical gap is the prime variable and shares 18.43% for the development of roundabout entry capacity. As compared with the Girabase formula (France), Brilon wu formula (Germany), and HCM 2010 models, the proposed MNLR model is quite reliable under low to medium ranges of traffic volumes. Roundabouts are a specialized form of an un-signalized intersection in which traffic moves in one direction around a central island. Direction of traffic, according to left-hand or right-hand driving rules, depends on the specific country. Roundabouts have been used as an effective intersection control measure to improve safety and operational performance under low to high circulating traffic flow conditions. As compared with other, signa-lized, intersections, roundabouts have several basic advantages, such as speed reduction of vehicles, less delay, pedestrian safety, aesthetics, and reduction of conflict points. A signalized intersection has 32 conflict points, whereas a roundabout with two circulating and entry lanes has 8 and 16 conflict points, respectively. Because of the increase in the use of roundabouts, an assessment regarding operational performance needs to be undertaken. Evaluation of capacity at roundabouts is an important aspect of operational performance that describes the present traffic scenario, level of service, delay, accidents, operational cost, and environmental issues. Under heterogeneous traffic conditions, vehicles of various kinds have varying physical and operational characteristics. In developing countries, driver behavior, vehicular characteristics (size, engine efficiency, and years of usage), and intersection geometric design vary significantly. The vehicle fleet is composed of heavy vehicles (HV), light motor vehicles (LMV), motor cycles/ scooters (MC/S), bicycles (BC) and human-drawn vehicles (HDV). These vehicles share the main carriageway without any physical or marked segregation. When there are vehicles of different types with varying static and dynamic characteristics, follow-the-lane discipline and the follow-the-leader concept become irrelevant. Under constraints of flow and space, small-sized vehicles try to move into the circulating area without following lane discipline. Also, HV forcibly merge into the circulating stream of traffic. These points reflect that the rule of priority is not respected under such a heterogeneous traffic condition. In these circumstances, the study of

Large IP backbone networks today are mostly deployed directly over sequences of point-to-point DWDM systems or chains of newer ROADM-based ultra long haul systems, interconnected by OEO regenerators. The next generation core optical network is moving toward an all-optical network architecture that is based on multi-degree ROADMs to reduce OEO regeneration cost as well as enabling automatic reconfigurability and dynamic restoration. In this paper, we study the restoration design in this new IP over reconfigurable all-optical network architecture to satisfy the resilience requirements for both IP and wavelength services. We propose two novel restoration schemes: 2-Phase Fast Reroute mechanism with optimized Traffic Engineering algorithm for restoring IP services and shared mesh restoration with standbys for restoring wavelength services. They both meet the requirement of sub-second restoration time and also maximize sharing among different failures with the objective of minimizing either overall capacity or overall cost. To further reduce the required restoration capacity in both IP layer and optical layer and address failures in both layers efficiently, we also propose an integrated IP-over-optical layer restoration strategy that enables sharing of restoration capacity among non-simultaneous failures across both IP and optical layers. Simulation results demonstrate significant improvements using our proposed schemes comparing with existing ones.

Este trabalho apresenta uma revisão bibliográfica sobre as características e melhores práticas
quanto a implantação de Rotatórias Modernas e, também, sobre os métodos usuais de avaliação
de desempenho de tráfego: determinístico e estocástico. Após uma breve descrição sobre
ambos, apresentam-se os critérios que justificam a escolha do modelo e programa utilizados.
Em seguida, descreve-se detalhadamente todas as etapas de levantamento de campo e posterior
compilação de dados, necessárias para microssimular com fidelidade o comportamento da
rotatória do estudo de caso, avaliando seu desempenho para os cenários de demanda atual e
de crescimento estimado, minorado e majorado, para os próximos 5, 10 e 20 anos. Os resultados
apresentados já no cenário atual pós-implantação, provam que o projeto da interseção
falha, comprometendo o escoamento do fluxo de veículos com destino à Cidade Universitária,
resultando em significativo impacto na fluidez do tráfego em seu entorno. Desta forma, três
alternativas práticas são sugeridas e simuladas para verificar sua influência quanto à melhoria
do desempenho da rotatória:(a) melhora de 15%; (b) melhora de 7,8%; (c) piora de 37,6%,
comprovando que a configuração recomendada da rotatória deve ser de duas faixas com uso de
Flare.