Academic literature on the topic 'Traffic flow - Urban areas'

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Journal articles on the topic "Traffic flow - Urban areas"

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Pradhan, R. K., S. Shrestha, and D. B. Gurung. "Mathematical modeling of mixed-traffic in urban areas." Mathematical Modeling and Computing 9, no. 2 (2022): 226–40. http://dx.doi.org/10.23939/mmc2022.02.226.

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Transportation is the means of mobility. Due to the growth in the population, rising traffic on road, delay in the movement of vehicles and traffic chaos could be observed in urban areas. Traffic congestion causes many social and economic problems. Because of the convenience and the quickness, motor-bikes gradually become the main travel mode of urban cities. In this paper, we extend the Lighthill–Whitham–Richards (LWR) traffic flow model equation into the mixed-traffic flow of two entities: car and motor-bike in a unidirectional single-lane road segment. The flow of cars is modeled by the advection equation and the flow of motor-bikes is modeled by the advection-diffusion equation. The model equations for cars and motor-bikes are coupled based on total traffic density on the road section, and they are non-dimensionalized to introduce a non-dimensional number widely known as Péclet number. Explicit finite difference schemes satisfying the CFL conditions are employed to solve the model equations numerically to compute the densities of cars and motor-bikes. The simulation of densities over various time instants is studied and presented graphically. Finally, the average densities of cars and motor-bikes on the road section are calculated for various values of Péclet numbers and mixed-traffic behavior are discussed. It is observed that the mixed-traffic behavior of cars and motor-bikes depends upon the Péclet number. The densities of motor-bikes and cars in the mixed-traffic flow approach the equilibrium state earlier in time for smaller values of Péclet number whereas densities take longer time to approach the equilibrium for the greater values of Péclet number.
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Liao, Zhuhua, Haokai Huang, Yijiang Zhao, Yizhi Liu, and Guoqiang Zhang. "Analysis and Forecast of Traffic Flow between Urban Functional Areas Based on Ride-Hailing Trajectories." ISPRS International Journal of Geo-Information 12, no. 4 (March 28, 2023): 144. http://dx.doi.org/10.3390/ijgi12040144.

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Urban planning and function layout have important implications for the journeys of a large percentage of commuters, which often make up the majority of daily traffic in many cities. Therefore, the analysis and forecast of traffic flow among urban functional areas are of great significance for detecting urban traffic flow directions and traffic congestion causes, as well as helping commuters plan routes in advance. Existing methods based on ride-hailing trajectories are relatively effective solution schemes, but they often lack in-depth analyses on time and space. In the paper, to explore the rules and trends of traffic flow among functional areas, a new spatiotemporal characteristics analysis and forecast method of traffic flow among functional areas based on urban ride-hailing trajectories is proposed. Firstly, a city is divided into areas based on the actual urban road topology, and all functional areas are generated by using areas of interest (AOI); then, according to the proximity and periodicity of inter-area traffic flow data, the periodic sequence and the adjacent sequence are established, and the topological structure is learned through graph convolutional neural (GCN) networks to extract the spatial correlation of traffic flow among functional areas. Furthermore, we propose an attention-based gated graph convolutional network (AG-GCN) forecast method, which is used to extract the temporal features of traffic flow among functional areas and make predictions. In the experiment, the proposed method is verified by using real urban traffic flow data. The results show that the method can not only mine the traffic flow characteristics among functional areas under different time periods, directions, and distances, but also forecast the spatiotemporal change trend of traffic flow among functional areas in a multi-step manner, and the accuracy of the forecasting results is higher than that of common benchmark methods, reaching 96.82%.
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Dong, Yu Bo. "Discussion on Urban Road Traffic Congestion Algorithm for Automatically Determining." Advanced Materials Research 926-930 (May 2014): 3790–93. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3790.

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Compared with the expressway, most of the traffic flow in urban road network can be denoted as interrupted traffic flow. Based on the current employed equipment for traffic flow collection and traffic signal control in urban roads, different types of traffic flow in urban roads are analyzed with the traffic flow arrival/departure model in transportation engineering. Mathematical models complying with traffic flow changes are utilized to match the traffic flow in both entry and exit road blocks, thus, enabled the automatic detection of traffic incident. This algorithm provides a measurement for the automatic judgment of urban road congestion and the expansion utility of intelligent transportation facilities in urban areas.
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Nemtanu, Florin, Ilona Madalina Costea, and Catalin Dumitrescu. "Spectral Analysis of Traffic Functions in Urban Areas." PROMET - Traffic&Transportation 27, no. 6 (December 17, 2015): 477–84. http://dx.doi.org/10.7307/ptt.v27i6.1686.

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The paper is focused on the Fourier transform application in urban traffic analysis and the use of said transform in traffic decomposition. The traffic function is defined as traffic flow generated by different categories of traffic participants. A Fourier analysis was elaborated in terms of identifying the main traffic function components, called traffic sub-functions. This paper presents the results of the method being applied in a real case situation, that is, an intersection in the city of Bucharest where the effect of a bus line was analysed. The analysis was done using different time scales, while three different traffic functions were defined to demonstrate the theoretical effect of the proposed method of analysis. An extension of the method is proposed to be applied in urban areas, especially in the areas covered by predictive traffic control.
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Qin, Jiayu, Gang Mei, and Lei Xiao. "Building the Traffic Flow Network with Taxi GPS Trajectories and Its Application to Identify Urban Congestion Areas for Traffic Planning." Sustainability 13, no. 1 (December 30, 2020): 266. http://dx.doi.org/10.3390/su13010266.

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Traffic congestion is becoming a critical problem in urban traffic planning. Intelligent transportation systems can help expand the capacity of urban roads to alleviate traffic congestion. As a key concept in intelligent transportation systems, urban traffic networks, especially dynamic traffic networks, can serve as potential solutions for traffic congestion, based on the complex network theory. In this paper, we build a traffic flow network model to investigate traffic congestion problems through taxi GPS trajectories. Moreover, to verify the effectiveness of the traffic flow network, an actual case of identifying the congestion areas is considered. The results indicate that the traffic flow network is reliable. Finally, several key problems related to traffic flow networks are discussed. The proposed traffic flow network can provide a methodological reference for traffic planning, especially to solve traffic congestion problems.
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Striewski, Sören, Ingo Thomsen, and Sven Tomforde. "Adaptive Approaches for Tidal-Flow Lanes in Urban-Road Networks." Future Transportation 2, no. 3 (June 27, 2022): 567–88. http://dx.doi.org/10.3390/futuretransp2030031.

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Every year, traffic congestion costs the global economy billions of dollars in lost productivity, particularly in urban areas. Traffic congestion is a complex problem, as traffic conditions may change at any time. Tidal-flow lanes can be utilised as a feasible traffic-congestion-mitigation strategy to balance the fluctuating traffic demands throughout the day. This paper proposes an adaptive-lane-reversal approach for tidal-flow lanes, to decrease the impact of traffic congestion in urban areas. In order to evaluate the adaptive approach under various traffic conditions, several algorithms and parameter sets are examined, using various network models and traffic demands. As a result, the total travel time of the vehicles in the various networks was decreased by up to 81%.
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Zambrano-Martinez, Jorge, Carlos Calafate, David Soler, Lenin-Guillermo Lemus-Zúñiga, Juan-Carlos Cano, Pietro Manzoni, and Thierry Gayraud. "A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas." Electronics 8, no. 7 (June 26, 2019): 722. http://dx.doi.org/10.3390/electronics8070722.

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Currently, one of the main challenges that large metropolitan areas must face is traffic congestion. To address this problem, it becomes necessary to implement an efficient solution to control traffic that generates benefits for citizens, such as reducing vehicle journey times and, consequently, environmental pollution. By properly analyzing traffic demand, it is possible to predict future traffic conditions, using this information for the optimization of the routes taken by vehicles. Such an approach becomes especially effective if applied in the context of autonomous vehicles, which have a more predictable behavior, thus enabling city management entities to mitigate the effects of traffic congestion and pollution, thereby improving the traffic flow in a city in a fully centralized manner. This paper represents a step forward towards this novel traffic management paradigm by proposing a route server capable of handling all the traffic in a city, and balancing traffic flows by accounting for present and future traffic congestion conditions. We perform a simulation study using real data of traffic congestion in the city of Valencia, Spain, to demonstrate how the traffic flow in a typical day can be improved using our proposed solution. Experimental results show that our proposed traffic prediction equation, combined with frequent updating of traffic conditions on the route server, can achieve substantial improvements in terms of average travel speeds and travel times, both indicators of lower degrees of congestion and improved traffic fluidity.
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Huang, Zhufei, Zihan Zhang, Haijian Li, Lingqiao Qin, and Jian Rong. "Determining Appropriate Lane-Changing Spacing for Off-Ramp Areas of Urban Expressways." Sustainability 11, no. 7 (April 8, 2019): 2087. http://dx.doi.org/10.3390/su11072087.

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Congestion has become a significant issue in recent years and has greatly affected the efficiency of urban traffic operation. Random and disorderly lane-changing behavior greatly reduces traffic capacity and safety. This paper is mainly concerned with the relationship of lane-changing spacing intervals provided by off-ramp facilities and traffic flow conditions. Through field investigations in Beijing, several typical lane-changing behaviors at off-ramp areas are analyzed. By using field traffic data and actual road geometry parameters, VISSIM-based micro-behavior simulations at off-ramp areas are implemented to obtain traffic flow conditions with different lane-changing spacing intervals and other model parameters, such as traffic volume and ratio of off-ramp vehicles. Then, the numerical relationships between traffic flow state and model parameters can be shown. The results show that with increasing traffic volume and the ratio of off-ramp vehicles, the lane-changing spacing interval required by vehicles should be increased. For the same ratio of off-ramp vehicles, if the traffic volume increases by 100 pcu/h/lane (pcu is a unit to stand for a standard passenger car), the corresponding lane-changing spacing interval should be increased by a spacing of 50–100 m to avoid increasing congestion. Based on the results of this paper, smart lane management can be implemented by optimizing lane-changing spacing intervals and lane-changing behaviors to improve traffic capacity.
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Kuang, Weiming, Shi An, and Huifu Jiang. "Detecting Traffic Anomalies in Urban Areas Using Taxi GPS Data." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/809582.

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Large-scale GPS data contain hidden information and provide us with the opportunity to discover knowledge that may be useful for transportation systems using advanced data mining techniques. In major metropolitan cities, many taxicabs are equipped with GPS devices. Because taxies operate continuously for nearly 24 hours per day, they can be used as reliable sensors for the perceived traffic state. In this paper, the entire city was divided into subregions by roads, and taxi GPS data were transformed into traffic flow data to build a traffic flow matrix. In addition, a highly efficient anomaly detection method was proposed based on wavelet transform and PCA (principal component analysis) for detecting anomalous traffic events in urban regions. The traffic anomaly is considered to occur in a subregion when the values of the corresponding indicators deviate significantly from the expected values. This method was evaluated using a GPS dataset that was generated by more than 15,000 taxies over a period of half a year in Harbin, China. The results show that this detection method is effective and efficient.
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J, Cynthia, G. Sakthi Priya, C. Kevin Samuel, Suguna M, Senthil J, and S. Abraham Jebaraj. "Traffic Flow Forecasting Using Machine Learning Techniques." Webology 18, no. 04 (September 28, 2021): 1512–26. http://dx.doi.org/10.14704/web/v18si04/web18295.

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Congestion due to traffic, results in wasted fuel, increase in pollution level, increase in travel time and vehicular queuing. Smart city initiatives are aimed to improve the quality of urban life. Intelligent Transportation System (ITS) provides solution for many smart city projects, as they capture real time data without any fixed infrastructure. The real-time prediction of traffic flow aids in alleviating congestion. Accurate and timely prediction on the future traffic flow helps individual travellers, public transport, and transport planning. Existing systems are designed to predict specific traffic parameters like weekday, weekend, and holidays. This research presents a machine learning based traffic flow forecasting for the city of Bloomington, US not with any precise parameter. The day-wise dataset for the 5 areas is taken from Jan 1, 2017 to Dec 31, 2019. The algorithm used for implementation is Support Vector Regression (SVR) and Long Short-Term Memory (LSTM). LSTM algorithm provides better traffic prediction with least root means square error value.
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Dissertations / Theses on the topic "Traffic flow - Urban areas"

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Kothuri, Sirisha Murthy. "Exploring Pedestrian Responsive Traffic Signal Timing Strategies in Urban Areas." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1934.

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The role of walking in the development of healthy, livable communities is being increasingly recognized. In urban areas, intersections represent locations where different modes converge, and are often viewed as deterrents to walking. This is due to the unwarranted and often unnecessary delays imposed by signal timing policies for pedestrians and increased potential for conflicts. Traditional signal timing design prioritizes vehicles over pedestrians leading to undesirable consequences such as large delays and risky pedestrian behaviors. Pedestrians are accommodated in a manner that is designed to cause least interruption to the flow of motor vehicles. This lack of pedestrian accommodation at signalized intersections is the focus of this dissertation. Understanding pedestrian attitudes and perceptions is important because it offers insights into actual crossing behavior at signalized intersections. An intercept survey of 367 crossing pedestrians was undertaken at four signalized intersections in Portland, Oregon, and binary logistic regression models were constructed to quantify the impacts of demographics, trip characteristics and type of infrastructure on pedestrian perceptions and attitudes regarding delay, crossing time and motivators for crossing decisions. Safety was found to have a larger effect than compliance on the decision to cross the street. Pedestrians at recall intersections expressed higher satisfaction with delay than at actuated intersections. Novel methods to measure pedestrian delay using 2070 signal controllers and Voyage software were developed. These methods have been adopted by the City of Portland to record actuation trends and delays at various intersections. In the absence of demand data, pedestrian push button actuations can be considered as a proxy for crossing demand. The micro-simulation software VISSIM was used to analyze delays resulting from varying pedestrian and vehicle volumes on a network of three intersections in Portland, Oregon. From a pedestrian perspective, free operation was found to be always beneficial due to lower pedestrian delays. However, from a system wide perspective, free operation was found to be beneficial only under low-medium traffic conditions from an overall delay reduction viewpoint, while coordinated operation showed benefits under heavy traffic conditions, irrespective of the volume of pedestrians. Control strategies were developed to identify the best mode of signal controller operation that produced the lowest overall average delay per user. A procedure to identify the optimal control strategy based on user inputs (major street volume to capacity ratios and rate of pedestrian phase serviced for the minor street) was developed. The procedure was applied to a network of three intersections in east Portland, OR and the findings were verified. This research offers significant contributions in the field of pedestrian research. The findings related to attitudes and perceptions of crossing pedestrians offer greater insights into pedestrian crossing behavior and add to the body of existing literature. The methods developed to obtain pedestrian actuations and delay data from signal controllers represent an easy and cost-effective way to characterize pedestrian service at intersections. The results pertaining to signal timing strategies represent an important step towards incorporating pedestrian needs at intersections and demonstrate how control strategies employed to benefit pedestrians could benefit the entire system.
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AGOSTI, ABRAMO. "MODELS OF TURBULENCE. APPLICATIONS TO PARTICULATE MIXING INDUCED BY TRAFFIC FLOW IN URBAN AREAS." Doctoral thesis, Università degli Studi di Milano, 2013. http://hdl.handle.net/2434/217169.

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In this work we address our attention to the estimation of the contribution of non-exhaust sources, like brake abrasion, tire and road wear and resuspension of particles, to the final PM air concentration; particularly we focus our investigation on the resuspension of PM deposited on road pavement surfaces and raised by the air turbulence produced by the vehicles flux, under urban and extra-urban traffic conditions. Our approach to the problem is based on modeling techniques. We refer to measurement data from literature to determine the selected empirical parameters contained in our models. Analytical models based on algebraic eddy diffusivity hypothesis are applied to describe the mean statistical component of flow generated by air recirculation inside a canyon and by the far-wake structure besides moving vehicles of simplified geometrical shapes. The analysis of the far wake solutions is suitable to the description of vehicle wakes interaction, which permits to apply our analysis to different driving cycles conditions. Numerical simulations based on finite element discretization of suitable two-equation turbulence models are employed to describe near-wake structures, which cause the strongest mixing of atmospheric pollutants and resuspension of road dust. These different components of turbulence fields at different scales of the street geometry are composed to define a set of operational and numerical models for the dispersion dynamics at the canyon scale of two classes of PM10 pollutants, corresponding to a Soot and a road dust components. The deposition and the resuspension of pollutants are described by resistance and filtration models on porous asphalts, inserting the corresponding terms in the dispersion equations as suitable boundary conditions on the ground. We estimate the resuspension fraction of traffic-related PM10 emissions at the tailpipe, through a simplified linear-emission model, considering representative data describing traffic statistics coming from empirical data. Profile laws of resuspension factors are drawn, for different vehicles geometries and velocities, and how resuspension changes with different asphalt characteristics. The results are applied to typical traffic situations in the city of Milan, studying the effect of implementations of different reduction scenarios to the total amount of traffic-related PM10 emissions. The results point at a new approach to the local PM10 reduction policies, based on more effective asphalt design and maintenance. Finally, we apply one of the dispersion operational models to the case of a congested urban traffic configuration in a canyon street, in order to obtain the pollutant spatial distribution.
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Slavin, Courtney Natasha. "The Relationship Between Traffic Signals and Pedestrian, Bicyclist and Transit User Exposure in Urban Areas." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/616.

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Improving the efficiency of traffic operations along arterials is currently a priority for many agencies as their roadway infrastructure is built out to the largest possible capacity within the urban environment. Many advanced systems are being implemented to optimize traffic signal timing. Air quality is typically not a consideration when these decisions are made. The relationship between exposure to air pollution and traffic signal timing has not been fully explored by other researchers. This study is the first research effort to combine detailed traffic signal timing data (at 5 second intervals) and air pollutant exposure data. Results show that longer green time along the busy arterial reduces pollutant levels, while increased volume per cycle increases pollutant levels. This research quantifies the factors that contribute to pedestrian, bicyclist, and transit user exposure at a busy intersection along an urban arterial. The factors include traffic signal timing, weather related variables, traffic volumes, and heavy vehicle and bus presence. Additionally, the impact of an adaptive traffic signal system on air quality is assessed to understand the implications of signal timing on air pollutant exposure.
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Ma, Xiaoyi [Verfasser], and Dieter [Akademischer Betreuer] Schramm. "Effects of Vehicles with Different Degrees of Automation on Traffic Flow in Urban Areas / Xiaoyi Ma ; Betreuer: Dieter Schramm." Duisburg, 2021. http://d-nb.info/123032271X/34.

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Andersson, Lovisa. "An application of Bayesian Hidden Markov Models to explore traffic flow conditions in an urban area." Thesis, Uppsala universitet, Statistiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385187.

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This study employs Bayesian Hidden Markov Models as method to explore vehicle traffic flow conditions in an urban area in Stockholm, based on sensor data from separate road positions. Inter-arrival times are used as the observed sequences. These sequences of inter-arrival times are assumed to be generated from the distributions of four different (and hidden) traffic flow states; nightly free flow, free flow, mixture and congestion. The filtered and smoothed probability distributions of the hidden states and the most probable state sequences are obtained by using the forward, forward-backward and Viterbi algorithms. The No-U-Turn sampler is used to sample from the posterior distributions of all unknown parameters. The obtained results show in a satisfactory way that the Hidden Markov Models can detect different traffic flow conditions. Some of the models have problems with divergence, but the obtained results from those models still show satisfactory results. In fact, two of the models that converged seemed to overestimate the presence of congested traffic and all the models that not converged seem to do adequate estimations of the probability of being in a congested state. Since the interest of this study lies in estimating the current traffic flow condition, and not in doing parameter inference, the model choice of Bayesian Hidden Markov Models is satisfactory. Due to the unsupervised nature of the problematization of this study, it is difficult to evaluate the accuracy of the results. However, a model with simulated data and known states was also implemented, which resulted in a high classification accuracy. This indicates that the choice of Hidden Markov Models is a good model choice for estimating traffic flow conditions.
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Mariotte, Guilhem. "Dynamic Modeling of Large-Scale Urban Transportation Systems." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSET010/document.

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La congestion en milieu urbain est un enjeu majeur que ce soit d’un point vue économique, social ou environnemental. À court et moyen terme, l’utilisation de la simulation dynamique du trafic routier peut permettre d’analyser et de guider des politiques d’optimisation des infrastructures existantes. Aujourd’hui, du fait de la complexité des systèmes de transport, les outils de modélisation classiques sont limités à des échelles géographiques peu étendues (de l’ordre du quartier). À grande échelle, le temps de calcul devient rapidement un facteur limitant tout comme le calibrage et la scénarisation. Néanmoins les dernières décennies ont vu l’apparition d’une nouvelle génération de modèles bien adaptés aux métropoles urbaines. Ceux-ci sont basés sur une relation phénoménologique entre la production de déplacements et le nombre de véhicules dans une zone spatiale d’un réseau routier, appelée Diagramme Fondamental de Zone (Macroscopic Fundamental Diagram, MFD). Cette relation, validée empiriquement sur de nombreuses villes, a permis d’étudier différentes méthodes de contrôle du trafic pour une ville entière, mais a été peu utilisée à des fins de prévision de la congestion. L’objectif de cette thèse est de proposer un premier outil opérationnel de simulation et d’analyse des grands réseaux de métropoles, en utilisant et développant les modèles de trafic basés sur la relation MFD. Cet outil doit posséder un cadre théorique cohérent qui puisse convenir à des applications telles que la prévision d’états de trafic, le développement de nouvelles politiques de contrôle, l’estimation de pollutions liées au trafic, etc. Les contributions de la thèse portent sur deux aspects. Le premier est l’analyse des propriétés mathématiques et physiques des modèles existants, en incluant une formalisation complète de la gestion de plusieurs longueurs de parcours au sein d’une même zone urbaine. En particulier, cette formalisation traite de la distinction des trajets internes à la zone et des problèmes de flux convergents et divergents pour les trajets traversant la zone lorsque la congestion se propage d’une zone à l’autre. Le deuxième aspect est la proposition d’un nouveau modèle basé sur la distance individuelle parcourue à l’intérieur d’une zone urbaine (trip-based). Cette approche permet d’individualiser les usagers (auparavant représentés sous forme de flux continus) et donc de définir plus finement leurs caractéristiques, en vue de coupler leurs déplacements à des modèles d’affectations sur différentes routes. Enfin, des exemples d’application illustrant diverses collaborations sont donnés en dernière partie de la thèse. La simulation du trafic sur l’aire urbaine du Grand Lyon (France) y est présentée, ainsi que de nouveaux modules de modélisation de la recherche de parking ou de contrôle périphérique. Cette thèse est partie intégrante d’un projet européen ERC intitulé MAGnUM : Approche multi-échelle et multimodale de la modélisation du trafic pour une gestion durable de la mobilité urbaine
Congestion in urban areas has become a major issue in terms of economic, social or environmental impact. For short or mid term, using dynamic road traffic simulation can help analyzing and providing guidelines to optimization policies of existing infrastructures. Today, because of the complexity of transport systems, classical modeling tools are limited to small geographical areas (of a district size). Computational time, together with simulation calibration, are notably very constraining at large scales. However, a new generation of models designed for metropolitan areas has arisen over the past decades. These models are based on a phenomenological relationship between travel production and the number of vehicles in a given spatial area of a road network, known as the Macroscopic Fundamental Diagram (MFD). This relationship, supported by empirical evidences from several cities around the world, has allowed the study of different traffic control schemes at a whole city scale, but was rarely used for traffic state forecasting. The aim of this PhD is to propose an efficient modeling tool, based upon the concept of MFD, to simulate and analyze traffic states in large metropolitan areas. The theoretical framework of this tool must be consistent and applicable for traffic state forecasting, development of new control policies, traffic emission estimation, etc. There are two major contributions in this PhD. The first one is analyzing the mathematical and physical properties of existing models, and formalizing the dynamics of several trip lengths inside the same urban zone. In particular, this formalization distinguishes between internal trips and trips crossing the zone. Flow merging and diverging issues are also addressed when congestion propagates from one zone to another. The second contribution is proposing a new trip-based model based on individual traveled distance. This approach allows to treat users independently (previously represented with continuous flows), and thus to define their characteristics more precisely to couple their trips with assignment models on different paths. Finally, examples of application from various collaborations are given in the last part of this thesis. It includes a simulation study of the Grand Lyon urban area (France), as well as new modules to simulate search-for-parking or perimeter control. This PhD is part of a European ERC project entitled MAGnUM: Multiscale and Multimodal Traffic Modeling Approach for Sustainable Management of Urban Mobility
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Goulart, Elisa Valentim. "Flow and dispersion in urban areas." Thesis, University of Reading, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.578021.

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The threat of deliberate or accidental releases of harmful substances in urban areas makes understanding atmospheric flow and dispersion important. When the source is located within the urban canopy the highest concentrations are in the short-range, i.e. less than lkm, where the dispersion is strongly affected by the presence of buildings. Understanding the processes that govern point source dispersion in the short range is important in order to develop a dispersion model for the use of emergency responders. Some questions are addressed based on this scenario: (i) What are the main flow mechanisms in urban areas? (ii) How does a ground source disperse in the short-range? (iii) How can we model short-range dispersion for fast response applications? To answer these questions data from direct numerical simulations (DNS) over arrays of buildings are analysed. In this study two regular building arrays are used (aligned and staggered) to determine the influence of geometry on near-field dispersion. The external flow is either parallel to or oblique (45°) to the building array. Analysis of the flow field reveals a number of flow features relevant for dispersion. Firstly, when the wind is oblique to the buildings the flow divides around them, thereby causing topological splitting. Secondly, the component of the wind parallel to the streets causes channelling along the street axis. Thirdly, the flow within intersections is complex and three-dimensional, especially for oblique wind directions. Fourthly, recirculation
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Grau, Mariani Rafael. "A demand-responsive traffic control system for urban areas." Doctoral thesis, Universitat Politècnica de Catalunya, 1995. http://hdl.handle.net/10803/399670.

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The goal of this Ph.D. Thesis is the design, development and testing of a 'well-engineered system' aimed at the demand-responsive traffic control of urban areas. Because of the author's background -software engineering-, a 'well-engineered system' means a system that is both efficient at performing its task in a wide range of conditions and also that has been built from the robust design's and ease-of-use's points of view. The work has proceed in four steps and, accordingly, this document has been divided in four parts that are briefly desc1ibed here. PART I is, mainly, an introduction to the subject. It introduces the concept of demand­ responsiveness in traffic control, providing a historical perspective from traditional fixed­ control systems to current modern demand-responsive systems. The part concludes with a study of areas where research and improvement is needed. All of these areas are considered in the following parts, where some solutions are proposed. PAR T II presents the design, development and preliminary tests of a demand­ responsive traffic control system, CARS V l, intended to operate in signalized urban areas: networks, arte1ials, and isolated intersections. A graphical user interface, X-Windows and DecWindows compliant, allows the user to specify network characteristics in a friendly and intuitive manner, without the need to be acquainted with the actual modeling. The system features an underlying simulation system and a prediction model based on real-time measured conditions, implements a centralized approach based on small variations, and has flexible detector positioning-and-number requirements. PART III presents the design of a simulation environment, named GETRAM, that solves the difficulties in testing CARS that were discussed at the end of the previous part. We have seen that these difficulties are inherent in the traffic engineer having to use diverse models in order to analyze a traffic network, and that there is the need for a system to salve it. GETRAM provides a unified framework integrating various types of traffic models and tools for traffic analysis, sharing a DataBase, a graphical editor and a mod le for results presentation. The traffic network can be partitioned into views, hierarchically organized polygons in the real world, so that, for example, a simulation model applies only to one of these restricted areas. Network statcs produced by one model can be used as a starting point by another modcl. I n order to ease the task of integrating a new model or analysis tool, a library of object-based high-level functions provide a view-aware access to the DataBase, maintaining consistency. Included in this Ph.D. thesis are the design of the whole environment -DataBase, G ETR AM API, and graphical editor - and the development of the DataBase and GETRAM API. PART IV starts from the demand-responsive traffic control system developed in PART II, CARS V l , and improves it in various respects. First, in order to ease the task of testing the system, it is integrated into the traffic modeling and analysis environment described in PART III. Second, certain parts that directly influence to the effectiveness of the system, such as control timing, adaptive control logics and communication with the controllers, are revised or totally redone. A suite of tests has been applied to the resulting system, CARS V2, in the four scenarios desc1ibed in PART 11. Finally, to further testing the system and taking advantage of the fact of having real-world data available, it is compared against a vehicle-actuated control at an isolated junction.
El objetivo de esta tesis es el diseño, desarrollo y test por simulación microscópica de un sistema autoadaptativo apto para cruces aislados, arterias y redes urbanas complejas. El sistema produce planes de control acíclicos y presenta unos requerimientos de tiempo real muy flexibles debidos a utilizar una nueva secuencia cíclica de tareas en la que se predice el estado del sistema a corto término antes de probar planes de control alternativos. Estas pruebas se realizan mediante un modelo interno de simulación que sigue un enfoque mesoscópico a base de paquetes de vehículos de velocidad variable, con el que se consigue modelizar la dinámica de colas de vehículos de forma más exacta que con los sistemas actualmente existentes. Esto da una ventaja, corroborada en los test, en condiciones de flujo altas, con lo que el sistema de controles es capaz de mantener una buena efectividad en un amplio rango de condiciones de tráfico. El sistema viene acompañado de un entorno de simulación y test que aporta un alto grado de integración y de facilidad de uso, a lo largo de todo el proceso de especificación de geometría, parámetros y ejecución de simulación se mantiene una vista de la red de tráfico altamente realista.
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Bostock, Adam K. "Prediction and reduction of traffic pollution in urban areas." Thesis, University of Nottingham, 1994. http://eprints.nottingham.ac.uk/14352/.

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This thesis is the result of five years research into road traffic emissions of air pollutants. It includes a review of traffic pollution studies and models, and a description of the PREDICT model suite and PREMIT emissions model. These models were used to evaluate environmentally sensitive traffic control strategies, some of which were based on the use of Advanced Transport Telematics (ATT). This research has improved our understanding of traffic emissions. It studied emissions of the following pollutants: carbon monoxide (CO), hydrocarbons (HC) and oxides of nitrogen (NOx). PREMIT modelled emissions from each driving mode (cruise, acceleration, deceleration and idling) and, consequently, predicted relatively complex emission characteristics for some scenarios. Results suggest that emission models should represent emissions by driving mode, instead of using urban driving cycles or average speeds. Emissions of NOx were more complex than those of CO and HC. The change in NOx, caused by a particular strategy, could be similar or opposite to changes in CO and HC. Similarly, for some scenarios, a reduction in stops and delay did not reduce emissions of NOx. It was also noted that the magnitude of changes in emissions of NOx were usually much less than the corresponding changes in CO and HC. In general, the traffic control strategies based on the adjustment of signal timings were not effective in reducing total network emissions. However, high emissions of pollutants on particular links could, potentially, be reduced by changing signal timings. For many links, mutually exclusive strategies existed for reducing emissions of CO and HC, and emissions of NOx. Hence, a decision maker may have to choose which pollutants are to be reduced, and which can be allowed to increase. The environmental area licensing strategy gave relatively large reductions in emissions of all pollutants. This strategy was superior to the traffic signal timing strategies because it had no detrimental impact on the efficiency of the traffic network and gave simultaneous reductions in emissions of CO, HC and NOx.
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Di, Sabatino Silvana. "Flow and pollutant dispersion in urban areas." Thesis, University of Cambridge, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615192.

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Books on the topic "Traffic flow - Urban areas"

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Hanks, James W. Roadway congestion in major urban areas, 1982 to 1987. College Station, Tex: Texas Transportation Institute, the Texas A&M University System, 1989.

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Vahl, H. G. Traffic calming through integrated urban planning. Paris: Amarcande, 1990.

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Engineers, Institute of Transportation. Designing walkable urban thoroughfares: A context sensitive approach. Washington, DC: Institute of Transportation Engineers, 2010.

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Institution of Highways and Transportation (Great Britain) and Great Britain. Dept. of Transport., eds. Roads and traffic in urban areas. London: HMSO, 1987.

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Urban spatial traffic patterns. London: Pion, 1987.

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National Research Council (U.S.). Transportation Research Board., ed. Traffic flow, capacity, roadway lighting, and urban traffic systems, 1990. Washington, D.C: Transportation Research Board, National Research Council, 1990.

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Schrank, David L. Estimates of urban roadway congestion, 1990. College Station, Tex: Texas Transportation Institute, Texas A&M University System, 1993.

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Schrank, David L. Estimates of urban roadway congestion, 1990. Washington, DC: Office of Traffic Management and Intelligent Vehicle Highway Systems, Federal Highway Administration, 1993.

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Fisk, C. S. Urban road traffic models for economic appraisal. Lambton Quay, Wellington: Transit New Zealand, 1992.

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H, Gartner Nathan, Improta Gennaro 1942-, and International Seminar on Urban Traffic Networks (2nd : 1992 : Capri, Italy), eds. Urban traffic networks: Dynamic flow modeling and control. Berlin: Springer-Verlag, 1995.

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Book chapters on the topic "Traffic flow - Urban areas"

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Hoch, Thomas, and Theodorich Kopetzky. "Energy-Efficient Internet of Things Solution for Traffic Monitoring." In Energy-Efficient and Semi-automated Truck Platooning, 129–41. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_10.

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AbstractRecent progress in video-based vehicle sensors allows for a detailed observation of road users on intersections in urban areas. By combining the measured real-life traffic situation with thorough traffic simulations, a cooperative system design for the dynamic management of traffic flow including vehicle platoons is possible. In this chapter, we describe our video-based traffic flow estimation system that we installed at a three-way intersection in the small city of Hallein, Austria. We show that the installed system is able to collect comprehensive information about the traffic situation in near real time, and that this information can be used to estimate traffic density and flows of cars and trucks with high precision.
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Carrese, Stefano, Stefano Gori, and Tommaso Picano. "Relationship between Parking Location and Traffic Flows in Urban Areas." In Advanced Methods in Transportation Analysis, 183–214. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-85256-5_9.

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Carpita, Maurizio, and Rodolfo Metulini. "Modelling the spatio-temporal dynamic of traffic flows with gravity models and mobile phone data." In Proceedings e report, 99–104. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-461-8.19.

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The analysis of origin-destination traffic flows may be useful in many contexts of application (e.g., urban planning, tourism economics) and have been commonly studied through the gravity model, which states that flows are proportional to ''masses" of both origin and destination, and inversely proportional to distance between them. Using data on the flow of mobile phone SIM among different aree di censimento, recorded hourly basis for several months and provided by FasterNet in the context of MoSoRe project, in this work we characterize and model the dynamic of such flows over the time in the strongly urbanized and flood-prone area of the Mandolossa (western outskirts of Brescia, northern Italy), with the aim of predicting the traffic flow during flood episodes. Whereas a traditional ”static” mass explanatory variable is represented by residential population (Pop), or by gross domestic product (GDP), here we propose to use a most accurate set of explanatory variables in order to better account for the dynamic over the time. First, we employ a time-varying mass variable represented by the number of city-users by area and by time period, which has been estimated from mobile phone data (provided by TIM) using functional data approach and already adopted to derive crowding maps for flood exposure. Secondly, we include in the model a proper set of factors such as areal and time dummies, and a novel set of indices related to (e.g.) the number and the type of streets, the number of offices, restaurants or cinemas, which may be retrieved from OpenStreetMap. The joint use of these two novel sets of explanatory variables should allow us to obtain a better linear fitting of the gravity model and a better traffic flow prediction for the flood risk evaluation.
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Singh, Sandeep, R. Vidya, Bishnu Kant Shukla, and S. Moses Santhakumar. "Analysis of Traffic Flow Characteristics Based on Area-Occupancy Concept on Urban Arterial Roads Under Heterogeneous Traffic Scenario—A Case Study of Tiruchirappalli City." In Lecture Notes in Civil Engineering, 69–84. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1303-6_6.

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Oprea, Cristina, Mircea Roşca, Şerban Stere, and Sergiu Olteanu. "Traffic Modeling in Urban Congested Areas." In Proceedings of the 4th International Congress of Automotive and Transport Engineering (AMMA 2018), 766–74. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94409-8_89.

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Formato, Enrico. "New Urbanization Phenomena and Potential Landscapes: Rhizomatic Grids and Asymmetrical Clusters." In Regenerative Territories, 135–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-78536-9_8.

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AbstractMore and more nowadays, the Circular Economy is at the heart of European public policies. As a result of the “Next Generation EU” Recovery Plans, a huge amount of financial resources will be available in the coming years to give shape the concept of “ecological transition". For that purpose, radical vision and operational concreteness are needed.In order to strengthen the territorial dimension of public policies aimed at ecological transition, the paper points to consider the status quo of the European territory, looking for recurring elements and differences. In this perspective, a return of “hard” urban studies, focusing on the issues of land ownership, land parcelling, infrastructural and urbanization procedures (and their relationships with the environment and the landscape) should be conducted at the European scale.A central role for the future of contemporary territories is recognized in the so-called “fringe area”, the part of the urban region where patterns of building development and unbuilt space interwave: its intermediary character, as a place between the compact city and the suburban countryside, makes this zone favourable to the collaboration between the two worlds. In addition, its easy accessibility from both the denser contexts and the outer areas makes it the perfect place to locate the equipment required to create short supply chains, so relevant for the circular economy and the ecological transition.These transition areas need to be rethought as new collective spaces of the contemporary city, areas for the proliferation of biodiversity, inhibited from settlement increase and subject to restrictions on car traffic. In them, the circular dimension of the new green economy could give shape to certain spatial conditions and new landscapes.Two main spatial models can describe this sustainable reform of the peri-urban territories. The first one assumes the figure of the “cluster”: a territorially and functionally defined region with one or more reference centres and an edge marking the discontinuity from other clusters. The second model is based on the figure of the “grid”: an unlimited mesh, which gives measure and organizes space according to a replicable and open system. This spatiality is built on a redundant and weak infrastructure, devoid of hierarchy, which can give rise to a sponge rich in pores, with neither internal nor external boundaries.The concept of the materiality also deals with the physical status of each context where the clusters of shortening flows would define local metabolisms, self-sufficient, marked by the use and recycling of what can be produced or “extracted” in the cluster itself. The closing of short supply chains for the use and recycling of materials, also with reference to the construction cycle and CDW recycling, would have direct consequences on the architectural character of the new arrangements: a kind of hyper-contextualism in which the landscape takes on grains, colours, materiality, closely linked to the local condition.Finally, a reflection on the rationales of the project is outlined. What is proposed, in fact, requires going beyond the traditional way in which the project has been conceived. In fact, these urban reconfiguration processes, structurally open to uncertainty, would take advantage of a programmatic choice of spatial incompleteness: a condition of “unfinished”, open to the accumulation over time of functions, forms, aggregations and densifications.
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McDonald, John F., Edmond L. d’Ouville, and Louie Nan Liu. "An Engineering Model of Traffic Flow." In Economics of Urban Highway Congestion and Pricing, 9–14. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5231-4_2.

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Pavlyuk, Dmitry. "Spatiotemporal Forecasting of Urban Traffic Flow Volatility." In Lecture Notes in Networks and Systems, 63–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68476-1_6.

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Hinz, Stefan, Steffen Suchandt, Diana Weihing, and Franz Kurz. "Traffic Data Collection with TerraSAR-X and Performance Evaluation." In Radar Remote Sensing of Urban Areas, 87–108. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3751-0_4.

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Mark Doctor, Patrick Hasson, Hillary Isebrands, and John McFadden. "Planning, Design, and Operations of Road Segments and Interchanges in Urban Areas." In Traffic Engineering Handbook, 283–320. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781119174738.ch9.

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Conference papers on the topic "Traffic flow - Urban areas"

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Wang, Yue, Ming Chen, and Aite Zhao. "Spatio-Temporal Correlation Augmented Model for Traffic Flow Prediction in Urban Areas." In ICBDT 2022: 2022 5th International Conference on Big Data Technologies. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3565291.3565299.

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Xing, Enhui, and Rui Wang. "Traffic Flow Characteristics of Urban Expressway in the Period of Ice and Snow of Cold Areas." In Seventh International Conference on Traffic and Transportation Studies (ICTTS) 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41123(383)41.

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Gonzalo Orden, Hernán. "Traffic calming measures and their effect on the variation of speed." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.4217.

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In recent years the number of deaths and serious injuries is decreasing in Spain, but, although the reduction outside the cities has been very strong, inside the urban areas, it has been smaller. This is especially hard if you look at the most vulnerable road users such as pedestrians and cyclists. In many accidents the speed factor appears closely linked not only to the number, but also to the severity of the accidents suffered inside the urban areas. Therefore, a reduction in the speed would improve the road safety. There are different measures known as "traffic calming measures" whose objectives are to reduce both the number and severity of accidents that occur on urban areas, by reducing the traffic flow through the streets, as well as the speed of the vehicles. However, the efficiency in speed reduction of each measure is not entirely known. That's the reason why they are implanted, in many cases, with no technical basis. The aim of this article is to show the effectiveness in reducing speed of some of the traffic calming measures. To this effect, field measurements were done on street sections with different types of traffic calming measures, in different places of a city of Burgos, in the north of Spain. These measurements were compared with other ones sited on other streets sections of similar characteristics but without traffic calming measures. Finally the conclusions are shown and some recommendations for improving their effectiveness are given.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4217
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Xess, Shruti, and Dr Akshey Bhargava. "Carrying capacity of Urban Transportation Networks: A case study of designed ideal city." In 7th GoGreen Summit 2021. Technoarete, 2021. http://dx.doi.org/10.36647/978-93-92106-02-6.12.

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With the rapid growth of urbanization, the population coupled with economy of most cities not only in India but globally is going through significant changes. One of the significant changes is relating to the fast development of transportation infrastructures in these areas which gives rise to a quick change on the travel behaviours. Changing life style along with the city’s expansion, increasing population growth in urban areas and vehicular growth demand the design of new transportation system which is capable of meeting the free flow of traffic by assessing the carrying capacities of road network to accommodate increasing growth of vehicles on a time scale. Carrying capacity is a commonly used concept to represent the maximum flows that can pass through the roads without traffic congestion in transportation system. The authors of the present paper have designed a hypothetical ideal city having population of 10000 people with projected population up to year 2051 and corresponding estimation of increased vehicles through well-defined methods. The authors have also designed the road network to accommodate estimated vehicles to ensure free flow of traffic without any congestion by assessing the carrying capacity of such road network through compatible simulation models.
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Biliszczuk, Jan, Hanna Onysyk, Marco Teichgraeber, and Robert Toczkiewicz. "Solutions to the problem of safe pedestrian traffic flow in cities." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.2354.

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<p>Heavy car traffic on main streets is nowadays a major problem of modern cities. In order to improve safety of pedestrians and cyclists and at the same time maintain fluent car traffic flow, a separation of those two traffic types may be desirable in some cases. This paper presents different possible solutions to this problem implemented in Polish cities.</p><p>Underpasses or footbridges across busy streets in urbanized areas can be an alternative to pedestrian crossings. Footbridges apart from ensuring safe communication, can be attractive architectural elements of urban space. The cable stayed footbridge in Jaworzno will not only facilitate safe pedestrian communication between a large housing estate and a sports hall, but is likely to become a landmark of the city.</p><p>An attractive proposal for pedestrians and cyclists moving along crowded and polluted streets are routes marked out on riverside areas. The footbridges connecting islands on the Odra River in Wrocław not only have enabled efficient communication, but also have changed the islands into easily accessible places of relaxation. Free communication along the river embankments intersected by busy routes can be facilitated by building additional passages under existing bridges. The subject of the competition in Poznań was a footbridge over the Warta River, located close to the historical part of the city. Its implementation, apart from the main function of connecting the university campus with the city centre, will create a great recreational place for students and all citizens.</p><p>An unusual supplement for traditional means of transport in urbanized area can be an aerial tramway line. “Polinka” cable car that connects both parts of the campus of Wrocław University of Science and Technology separated by the Odra River have turned out to be an unconventional and attractive alternative to a typical footbridge.</p>
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Jang, Dae-Sung, Corey A. Ippolito, Shankar Sankararaman, and Vahram Stepanyan. "Concepts of Airspace Structures and System Analysis for UAS Traffic flows for Urban Areas." In AIAA Information Systems-AIAA Infotech @ Aerospace. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2017. http://dx.doi.org/10.2514/6.2017-0449.

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Kosovac, Amel, Muharem Šabić, Ermin Muharemović, and Edvin Šimić. "Shipment delivery challenges using unmanned aerial vehicles." In INTERNATIONAL CONFERENCE ON ADVANCES IN TRAFFIC AND COMMUNICATION TECHNOLOGIES. University of Sarajevo - Faculty of Traffic and Communications, 2022. http://dx.doi.org/10.59478/atct.2022.22.

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A UAV (Unmanned Aerial Vehicle) is an unmanned aerial vehicle or aircraft that can be monitored remotely or flown independently using a pre-programmed flight plan. Simply, a drone is a selfpropelled vehicle heavier than air. From their beginnings and first forms to modern drones as we know them today, people have discovered many areas for their application. As the power and carrying capacity of drones has grown, so does the possibility of using them for different purposes such as logistics and postal services. The main advantage of drones in urban areas is the independence from road infrastructure and fast delivery, but several challenges need to be addressed for this type of delivery to be competitive with other modes. Many projects have dealt with this topic, but none of them has widespread use to this day. In this paper, we will present the basic challenges that arise in the use of drones for shipment delivery. The paper will present activities that should be prioritized to make a competitive type of service. The paper will present also the advantages over other types of shipment delivery and the current limitation with a future possible research area.
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Attanasi, Alessandro, Lorenzo Meschini, Marco Pezzulla, Gaetano Fusco, Guido Gentile, and Natalia Isaenko. "A hybrid method for real-time short-term predictions of traffic flows in urban areas." In 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). IEEE, 2017. http://dx.doi.org/10.1109/mtits.2017.8005637.

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Kmoniček, Hrvoje, and Filip Ruška. "Changes in traffic infrastructure with the arrival of autonomous vehicles." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1074.

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Autonomous vehicles represent a significant step forward in traffic safety and efficiency. Although it will be quite some time before all vehicles on public roads are autonomous, it is certainly advisable to consider the changes that will need to be introduced to traffic and traffic infrastructure. Autonomous vehicles will significantly increase the efficiency and use of public transportation and car-sharing, which will ultimately mean fewer cars on the roads and less need for parking in urban areas, or their conversion into a type of waiting area. Also, fewer vehicles, whose software has a drastically faster reaction time and much better control of the vehicle, will also mean less traffic jams, greater intersection flow, less need to channel traffic in traffic lanes and will remove traffic lights almost entirely out of use. This paper will look at the form of transport infrastructure and its variants in the case of mixed traffic with autonomous vehicles and drivers, as well as the situation with fully autonomous traffic without people behind the wheel.
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Olayode, O. I., L. K. Tartibu, and M. O. Okwu. "Application of Adaptive Neuro-Fuzzy Inference System Model on Traffic Flow of Vehicles at a Signalized Road Intersections." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70956.

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Abstract In recent years, most traffic accidents and congestions usually occur at road intersections in urban areas where the vehicle speed is high. This has necessitated the need for intelligent road transport systems and high-level algorithms to unravel the problem. In this study, the South Africa Road transportation system has been used as a case study to address traffic flow solutions at signalized road intersections using traffic flow variables such as traffic density, speed of vehicles, and traffic volume as decision variables. This paper focuses on using a hybrid creative algorithm based on signalized traffic flow to address the constant repetitive traffic congestion problem. The proposed hybrid algorithm is the adaptive neuro-fuzzy inference system (ANFIS). The speed of vehicles within the investigation period, the traffic density of the road network, and the traffic volume of vehicles on the road were used as input and output variables, respectively. Triangular membership function and Gaussian membership function were used for input and output variables, and rules were developed based on available traffic flow parameters. The result of the ANFIS model showed a training and testing performance of 0.8722 and 0.9370, respectively. This training and testing results showed that the ANFIS model is an effective model for optimizing traffic flow at signalized road intersections.
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Reports on the topic "Traffic flow - Urban areas"

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Kothuri, Sirisha. Exploring Pedestrian Responsive Traffic Signal Timing Strategies in Urban Areas. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1933.

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Slavin, Courtney. The Relationship Between Traffic Signals and Pedestrian, Bicyclist and Transit User Exposure in Urban Areas. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.616.

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Kodupuganti, Swapneel R., Sonu Mathew, and Srinivas S. Pulugurtha. Modeling Operational Performance of Urban Roads with Heterogeneous Traffic Conditions. Mineta Transportation Institute, January 2021. http://dx.doi.org/10.31979/mti.2021.1802.

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The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.
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Kumar, Kaushal, and Yupeng Wei. Attention-Based Data Analytic Models for Traffic Flow Predictions. Mineta Transportation Institute, March 2023. http://dx.doi.org/10.31979/mti.2023.2211.

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Traffic congestion causes Americans to lose millions of hours and dollars each year. In fact, 1.9 billion gallons of fuel are wasted each year due to traffic congestion, and each hour stuck in traffic costs about $21 in wasted time and fuel. The traffic congestion can be caused by various factors, such as bottlenecks, traffic incidents, bad weather, work zones, poor traffic signal timing, and special events. One key step to addressing traffic congestion and identifying its root cause is an accurate prediction of traffic flow. Accurate traffic flow prediction is also important for the successful deployment of smart transportation systems. It can help road users make better travel decisions to avoid traffic congestion areas so that passenger and freight movements can be optimized to improve the mobility of people and goods. Moreover, it can also help reduce carbon emissions and the risks of traffic incidents. Although numerous methods have been developed for traffic flow predictions, current methods have limitations in utilizing the most relevant part of traffic flow data and considering the correlation among the collected high-dimensional features. To address this issue, this project developed attention-based methodologies for traffic flow predictions. We propose the use of an attention-based deep learning model that incorporates the attention mechanism with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks. This attention mechanism can calculate the importance level of traffic flow data and enable the model to consider the most relevant part of the data while making predictions, thus improving accuracy and reducing prediction duration.
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Tran, My-Thu, and Bo Yang. Using Thermal Remote Sensing to Quantify Impact of Traffic on Urban Heat Islands during COVID. Mineta Transportation Institute, April 2023. http://dx.doi.org/10.31979/mti.2023.2207.

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A three-month lockdown in the U.S. at the beginning of the COVID-19 outbreak in 2020 greatly reduced the traffic volume in many cities, especially large metropolitan areas such as the San Francisco Bay Area. This research explores the impact of transportation on climate change by using remote sensing technology and statistical analysis during the COVID-19 lockdown. Using thermal satellite data, this research measures the intensity of the urban heat island, the main driver for climate change during the urbanization process. The research team acquired morning and afternoon MODIS data in the same periods in 2019 before the pandemic and 2020 during the pandemic. MODIS imagery provides a wall-to-wall land surface temperature map to precisely measure the dynamics of the urban heat effect. In situ meteorological data were also acquired to build an urban surface energy budget and construct statistical models between solar radiation and the intensity of heat dynamics. The team implemented this urban heat budget in six counties in Northern California. This research quantifies the impact of lockdown policies on heat intensity in urban areas and human mobility in the context of COVID-19 and future pandemics. The quantitative results obtained in this study provide critical information for analyses of climate change impact on an urban scale.
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Lin, Pei-Sung. Coordinated Pre-Preemption of Traffic Signals to Enhance Railroad Grade Crossing Safety in Urban Areas and Estimation of Train Impacts to Arterial Travel Time Delay. Tampa, FL: University of South Florida, January 2004. http://dx.doi.org/10.5038/cutr-nctr-rr-2014-06.

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Siebke, Christian, Maximilian Bäumler, Madlen Ringhand, Marcus Mai, Felix Elrod, and Günther Prokop. Report on integration of the stochastic traffic simulation. Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.246.

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As part of the AutoDrive project, the OpenPASS framework is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. This framework was adapted and further developed. The deliverable D5.13 deals with the construction of the stochastic traffic simulation. At this point of the process, the theoretical design aspects of D4.20 are implemented. D5.13 explains the operating principles of the different modules. This includes the foundations, boundary conditions, and mathematical theory of the traffic simulation.
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Siebke, Christian, Maximilian Bäumler, Madlen Ringhand, Marcus Mai, Felix Elrod, and Günther Prokop. Report on design of modules for the stochastic traffic simulation. Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.245.

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As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).
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Adsit, Sarah E., Theodora Konstantinou, Konstantina Gkritza, and Jon D. Fricker. Public Acceptance of INDOT’s Traffic Engineering Treatments and Services. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317280.

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As a public agency, interacting with and understanding the public’s perspective regarding agency activities is an important endeavor for the Indiana Department of Transportation (INDOT). Although INDOT conducts a biennial customer satisfaction survey, it is occasionally necessary to capture public perception regarding more specific aspects of INDOT’s activities. In particular, INDOT needs an effective way to measure and track public opinions and awareness or understanding of a select set of its traffic engineering practices. To evaluate public acceptance of specific INDOT traffic engineering activities, a survey consisting of 1.000 adults residing within the State of Indiana was conducted. The survey population was representative in terms of age and gender of the state as of the 2010 U.S. Census. The survey was administered during the months of July and August 2020. Public awareness regarding emerging treatments not currently implemented in Indiana is low and opposition to the same new technologies is prominent. Older or female drivers are less likely to be aware of emerging treatments, and older drivers are more likely to oppose potential implementation of these treatments. Although roundabouts are commonplace in Indiana, multi-lane roundabouts remain controversial among the public. Regarding maintenance and protection of traffic during work zones and considering full or partial roadway closure, public preference is for partial closure; this preference is stronger in rural areas. The public equally agrees and disagrees that INDOT minimizes construction related traffic delays. Approximately 76% of Indiana drivers believe themselves to above average drivers, while an additional 23% believe themselves to be average. Driver perceptions of average highway speeds speed are not aligned with posted speed limit as the perceived average speed on Indiana’s urban freeways and rural and urban state highways is considerably higher than the actual speed limit.
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Ringhand, Madlen, Maximilian Bäumler, Christian Siebke, Marcus Mai, and Felix Elrod. Report on validation of the stochastic traffic simulation (Part A). Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.242.

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This document is intended to give an overview of the human subject study in a driving simulator that was conducted by the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD) to provide the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD with the necessary input for the validation of a stochastic traffic simulation, especially for the parameterization, consolidation, and validation of driver behaviour models. VPSY planned, conducted, and analysed a driving simulator study. The main purpose of the study was to analyse driving behaviour and gaze data at intersections in urban areas. Based on relevant literature, a simulated driving environment was created, in which a sample of drivers passed a variety of intersections. Considering different driver states, driving tasks, and traffic situations, the collected data provide detailed information about human gaze and driving behaviour when approaching and crossing intersections. The collected data was transferred to LKT for the development of the stochastic traffic simulation.
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