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Assessment of traffic noise pollution in developing countries is complex due to heterogeneity in traffic conditions like traffic volume, road width, honking, etc. To analyze the impact of such variables, a research study was carried out on a national highway passing from an urban agglomeration. Traffic volume and noise levels (L₁₀, L_min, L_max, L_eq and L₉₀) were measured during morning and evening peak hours. Contribution of noise by individual vehicle was estimated using passenger car noise unit. Extent of noise pollution and impact of noisy vehicles were estimated using noise pollution level and traffic noise index, respectively. Noise levels were observed to be above the prescribed Indian and International standards. As per audio spectrum analysis of traffic noise, honking contributed an additional 3–4 dB(A) noise. Based on data analysis, a positive relationship was observed between noise levels and honking while negative correlation was observed between noise levels and road width. The study suggests that proper monitoring and analysis of traffic data is required for better planning of noise abatement measures.

Geographical information system (GIS)-based noise simulation software (N-GNOIS) has been developed to simulate the noise scenario due to point and mobile sources considering the impact of geographical features and meteorological parameters. These have been addressed in the software through attenuation modules of atmosphere, vegetation and barrier. N-GNOIS is a user friendly, platform-independent and open geospatial consortia (OGC) compliant software. It has been developed using open source technology (QGIS) and open source language (Python). N-GNOIS has unique features like cumulative impact of point and mobile sources, building structure and honking due to traffic. Honking is the most common phenomenon in developing countries and is frequently observed on any type of roads. N-GNOIS also helps in designing physical barrier and vegetation cover to check the propagation of noise and acts as a decision making tool for planning and management of noise component in environmental impact assessment (EIA) studies.

Traffic noise barriers are one of the most important ways of environmental noise pollution control. Profiled barriers are one of the most successful noise control screens. A simple mathematical model representation of the zones behind rigid and absorbent barriers with the highest insertion loss using the destructive effect of the indirect path via barrier image is introduced. The results are compared with the results of a verified two-dimensional (2D) BEM in a wide field behind those barriers. Field measurements for the model near a highway in a megacity were also tested. A very good agreement between the results has been achieved. In this method, effective height is used for any different profile barrier. Since the highway dominant noise frequency was found to be at 125 Hz 1/3-octave band center frequency, the presented model in this study showed that the best place for installing a T-shaped barrier is 10.5m from the target receiver. The introduced model is very simple and fast and could be used for choosing the best location of profiled barriers to achieve the highest performance with no additional cost.

We introduce a model of information packet transport on networks in which the packets are posted by a given rate and move in parallel according to a local search algorithm. By performing a number of simulations we investigate the major kinetic properties of the transport as a function of the network geometry, the packet input rate and the buffer size. We find long-range correlations in the power spectra of arriving packet density and the network's activity bursts. The packet transit time distribution shows a power-law dependence with average transit time increasing with network size. This implies dynamic queuing on the network, in which many interacting queues are mutually driven by temporally correlated packet streams.

Swarm intelligence is widely recognized as a powerful paradigm of self-organized optimization, with numerous examples of successful applications in distributed artificial intelligence. However, the role of physical interactions in the organization of traffic flows in ants under crowded conditions has only been studied very recently. The related results suggest new ways of congestion control and simple algorithms for optimal resource usage based on local interactions and, therefore, decentralized control concepts. Here, we present a mathematical analysis of such concepts for an experiment with two alternative ways with limited capacities between a food source and the nest of an ant colony. Moreover, we carry out microscopic computer simulations for generalized setups, in which ants have more alternatives or the alternative ways are of different lengths. In this way and by variation of interaction parameters, we can get a better idea of how powerful congestion control based on local repulsive interactions may be. Finally, we discuss potential applications of this design principle to routing in traffic or data networks and machine usage in supply systems.

We report a study of the correlations among topological, weighted and spatial properties of large infrastructure networks. We review the empirical results obtained for the air-transportation infrastructure that motivates a network modeling approach which integrates the various attributes of this network. In particular, we describe a class of models which include a weight-topology coupling and the introduction of geographical attributes during the network evolution. The inclusion of spatial features is able to capture the appearance of non-trivial correlations between the traffic flows, the connectivity pattern and the actual distances of vertices. The anomalous fluctuations in the betweenness-degree correlation function observed in empirical studies are also recovered in the model. The presented results suggest that the interplay between topology, weights and geographical constraints is a key ingredient in order to understand the structure and evolution of many real-world networks.

Street networks play a crucial role in the emergence of vehicular traffic. Here we present an experimental analysis of the street networks of several European cities (London, Paris, Rome, Modena). This analysis evidences the existence of universal properties in the morphology of different cities, which is captured by a model for the dynamics of city growth. Then, we discuss the implications of our findings for the development of city evacuation plans, whose efficiency is of paramount importance for cities threatened by natural hazards, such as volcanoes.

This contribution proposes a method to make agents in a microscopic simulation of pedestrian traffic walk approximately along a path of estimated minimal remaining travel time to their destination. Usually models of pedestrian dynamics are (implicitly) built on the assumption that pedestrians walk along the shortest path. Model elements formulated to make pedestrians locally avoid collisions and intrusion into personal space do not produce motion on quickest paths. Therefore a special model element is needed, if one wants to model and simulate pedestrians for whom travel time matters most (e.g. travelers in a station hall who are late for a train). Here such a model element is proposed, discussed and used within the Social Force Model.

Real time Internet traffic such as Voice over IP (VoIP) is difficult to estimate and simulate. Since the process is non-ergodic we must use ensemble averages rather than time averages, and for combinations of sources the simulation time can be excessive. We give some analytical results for Constant Bit Rate (CBR) traffic for the n*D/D/I queue, and for a CBR queue with varying source rates we present an expression for the Interval of Significance (IoS). This is the minimum number of time slots necessary to simulate the traffic, important because of the considerable computation time often involved in simulating this queue. Our results help in dimensioning networks for CBR services.