Congestion Model Research Articles

Methodologies for Traffic Congestion Prediction for a IoT Based Smart City Using Machine Learning and CNN

This paper aims at providing a machine learning model for the traffic congestion for Iot based smart city. We assume that the city is well equipped with the sensors on the streets and all the necessary parts of the city. The convolutionneural networks (CNN) and various machine learning classification and prediction algorithms are used to check which algorithm gives more accuracy for the data set generated.

Equilibrium in a dynamic model of congestion with large and small users

Individual users of transportation facilities often control a significant share of total traffic. Examples include airlines, rail and maritime freight shippers, urban goods delivery companies, taxi companies, and ride-sharing companies. These users have an incentive to internalize the congestion delays their own vehicles impose on each other by adjusting the timing of their trips. We investigate simultaneous trip-timing decisions by large users and small users in a dynamic model of congestion. Unlike previous work, we allow for heterogeneity of trip-timing preferences and for the presence of small users such as individual commuters and fringe airlines. We derive the optimal fleet departure schedule for a large user as a best-response to the aggregate departure rate of other users. We show that when the vehicles in a large user’s fleet have sufficiently diverse preferred arrival times, there may exist a pure-strategy Nash-equilibrium (PSNE) in which the large user schedules vehicles when there is a queue. This highlights that the problem of non-existence of a PSNE identified in Silva et al. (2016) for the case of symmetric large users hinges on the assumption that all vehicles in each fleet have the same preferred arrival time. We also develop some examples to identify under what conditions a PSNE exists, and when the large user departs. The examples illustrate how self-internalization of congestion by a large user can affect the nature of equilibrium and the travel costs that it and other users incur.

Quantitative estimation of extravascular lung water volume and preload by dynamic 15O-water positron emission tomography.

Left ventricular filling pressure (preload) can be assessed by pulmonary capillary wedge pressure (PCWP) during pulmonary arterial catheterization (PAC). An emerging method [pulse indexed contour cardiac output (PICCO)] can estimate preload by global end-diastolic volume (GEDV) and congestion as extravascular lung water (EVLW) content. However, no reliable quantitative non-invasive methods are available. Hence, in a porcine model of pulmonary congestion, we evaluated EVLW and GEDV by positron emission tomography (PET). The method was applied in 35 heart failure (HF) patients and 9 healthy volunteers. Eight pigs were studied. Pulmonary congestion was induced by a combination of beta-blockers, angiotensin-2 agonist and saline infusion. PAC, PICCO, computerized tomography, and 15O-H2O-PET were performed. EVLW increased from 521 ± 76 to 973 ± 325 mL (P < 0.001) and GEDV from 1068 ± 170 to 1254 ± 85 mL (P < 0.001). 15O-H2O-PET measures of EVLW increased from 566 ± 151 to 797 ± 231 mL (P < 0.001) and GEDV from 364 ± 60 to 524 ± 92 mL (P < 0.001). Both EVLW and GEDV measured with PICCO and 15O-H2O-PET correlated (r2 = 0.40, P < 0.001; r2 = 0.40, P < 0.001, respectively). EVLW correlated with Hounsfield units (HU; PICCO: r2 = 0.36, P < 0.001, PET: r2 = 0.46, P < 0.001) and GEDV with PCWP (PICCO: r2 = 0.20, P = 0.01, PET: r2 = 0.29, P = 0.002). In human subjects, measurements were indexed (I) for body surface area. Neither EVLWI nor HU differed between chronic stable HF patients and healthy volunteers (P = 0.11, P = 0.29) whereas GEDVI was increased in HF patients (336 ± 66 mL/m2 vs. 276 ± 44 mL/m2, P = 0.01). The present study demonstrates that 15O-H2O-PET can assess pulmonary congestion and preload quantitatively. Hence, prognostic information from 15O-H2O-PET examinations should be evaluated in clinical trials.

Long-term memory-induced synchronisation can impair collective performance in congested systems

We investigate the hypothesis that long-term memory in populations of agents can lead to counterproductive emergent properties at the system level. Our investigation is framed in the context of a discrete, one-dimensional road-traffic congestion model: we investigate the influence of simple cognition in a population of rational commuter agents that use memory to optimise their departure time, taking into account congestion delays on previous trips. Our results differ from the well-known minority game in that crowded slots do not carry any explicit penalty. We use Markov chain analysis to uncover fundamental properties of this model and then use the gained insight as a benchmark. Then, using Monte Carlo simulations, we study two scenarios: one in which myopic” agents only remember the outcome (delay) of their latest commute, and one in which their memory is practically infinite. We show that there exists a trade-off, whereby myopic memory reduces congestion but increases uncertainty, while infinite memory does the opposite. We evaluate the performance against the optimal distribution of departure times (i.e. where both delay and uncertainty are minimised simultaneously). This optimal but unstable distribution is identified using a genetic algorithm. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Equilibrium between Road Traffic Congestion and Low-Carbon Economy: A Case Study from Beijing, China

China has allocated low-carbon targets into all regions and trades, and road traffic also has its own emission reduction targets. Congestion may increase carbon emissions from road traffic. It is worthwhile to study whether it is possible to achieve the goal of road traffic reduction by controlling congestion; that is, to achieve the equilibrium between traffic congestion and a low-carbon economy. The innovation of this paper is mainly reflected in the innovative topic selection, the introduction of a traffic index, and the establishment of the first traffic congestion and low-carbon economic equilibrium model. First, the relevant calculation method of the traffic index is introduced, and the traffic index is used to quantify the traffic congestion degree. Using the traffic index, GDP, and road passenger traffic volume, a nonlinear regression model of road traffic carbon emissions is constructed. Then, the calculation method of the carbon emission intensity of road traffic in the region is proposed. The equilibrium model of traffic congestion and a low-carbon economy is constructed to look for the degree of road traffic congestion that may occur under the permitted carbon emission intensity. Taking Beijing, where electric vehicles account for less than 3% of the total vehicles, as an example, it is difficult to achieve the equilibrium target between road traffic congestion and a low-carbon economy by alleviating traffic congestion in 2020. If the target of traffic carbon emission reduction in 2020 is adjusted from 40%–45% to 19.7% based on 2005, the equilibrium will be achieved. A negative correlation between road traffic carbon emissions and the reciprocal of the traffic index (1/TI) is found after eliminating the effects of GDP and PTV (road passenger traffic volume). As the traffic index decreases by units, the carbon emission reduction accelerates. The results show that carbon reduction targets cannot be simply allocated to various industries. The results of the research on the degree of the impact of traffic congestion on carbon emissions can be used as a basis for carbon reduction decisions of the traffic sector. The research method of this paper can provide a reference for the study of the equilibrium of traffic congestion and a low-carbon economy in other regions.

Regulating Dynamic Congestion Externalities With Tradable Credit Schemes: Does a Unique Equilibrium Exist?

Tradeable credit schemes offer a potentially efficient, revenue-neutral policy alternative to classical dynamic pricing of congestion externalities. We show in this paper that the resulting equilibrium may not be unique for particular models of congestion, including the first-best solution for the conventional Vickrey’s bottleneck model. This can have substantial detrimental impacts on social welfare and social acceptance of tradable credit schemes. The reason underlying this result is that the credit supply-demand condition can be satisfied for a continuum of credit prices. This is because any marginal change in the credit price will be matched by a compensating change in queuing times, keeping user price fixed but deviating from the first-best optimum in which no queueing should occur. We find that the problem of non-uniqueness does not occur for the well-known dynamic flow congestion model proposed by Chu. A unique equilibrium can be obtained in the bottleneck model if the buying and selling of credits with a bank is allowed, against a pre-determined price. Credits are then still tradeable so that the use can deviate from the initial distribution, but the credit price is determined by the perfectly elastic demand and supply from the bank.

Congestion Control for Cloud Gaming Over UDP Based on Round-Trip Video Latency

We describe a network congestion control mechanism for cloud gaming (CG) platforms based on the user datagram protocol (UDP). To minimize the contribution of the downstream transmission delay to the total end-to-end latency in the interaction-perception loop, we first define the round-trip video latency (RTVL) and develop a congestion model. Based on them, we design and implement an adaptation strategy that detects the early stages of congestion to prevent high values of RTVL and network bufferbloat, thus avoiding packet losses. Using data measured from the network, our strategy modifies the target output bitrate of the video encoder to throttle down or upto the data flow sent by the server to the client. In the presence of sudden downstream channel capacity drops of over 40%, our algorithm reactively manages to satisfy the key CG requirements for interactive games by entirely avoiding the packet losses and keeping the RTVL below 100 ms. In reasonably stable network conditions, our algorithm proactively keeps exploring for higher bitrates and building a “network state dictionary,” due to which it achieves an effective downstream channel capacity use of ~95%.

Predictive Vehicle Route Optimization in Intelligent Transportation Systems

Through the adoption of dedicated short-range communication (DSRC) wireless communication technology, intelligent transportation systems (ITS) will spur a new revolution in the U.S. transportation system. This paper is structured around providing drivers with the least-congested transportation route choices enabled by the ITS-envisioned vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and infrastructure-to-vehicle (I2V) communication platforms. Recent research in vehicle navigation systems has proposed energy consumption and emission optimized routing methodologies using historical traffic data modeling. More than 50% of congestion in U.S. cities is nonrecurring congestion. Nonrecurring congestion reduces the availability of the traffic network, thus rendering historical traffic data-based systems insufficient in more than 50% of the cases. Real-time traffic data modeling provides an enhanced performance in traffic congestion assessment; however, greater performance is expected with a predictive traffic congestion model with increased certainty. This paper compares the conventional shortest path and fastest path vehicle routing methodologies and establish the improvement for environmentally friendly routing in a dynamic and predictive cost dependent traffic network based on Petri Net Modeling. The proposed routing algorithm is validated using a computer-based tool of choice.

Improved distributed algorithms for coloring interval graphs with application to multicoloring trees

We give a distributed (1+ϵ)-approximation algorithm for the minimum vertex coloring problem on interval graphs, which runs in the LOCAL model and operates in O(1ϵlog⁎⁡n) rounds. If nodes are aware of their interval representations, then the algorithm can be adapted to the CONGEST model using the same number of rounds. Prior to this work, only constant factor approximations using O(log⁎⁡n) rounds were known [1]. Linial's ring coloring lower bound implies that the dependency on log⁎⁡n cannot be improved. We further prove that the dependency on 1ϵ is also optimal.To obtain our CONGEST model algorithm, we develop a color rotation technique that may be of independent interest. We demonstrate that color rotations can also be applied to obtain a (1+ϵ)-approximate multicoloring of directed trees in O(1ϵlog⁎⁡n) rounds.

OLYMPUS v1.0: development of an integrated air pollutant and GHG urban emissions model – methodology and calibration over greater Paris

Abstract. Air pollutants and greenhouse gases have many effects on health, the economy, urban climate and atmospheric environment. At the city level, the transport and heating sectors contribute significantly to air pollution. In order to quantify the impact of urban policies on anthropogenic air pollutants, the main processes leading to emissions need to be understood: they principally include mobility for work and leisure as well as household behavior, themselves impacted by a variety of social parameters. In this context, the OLYMPUS modeling platform has been designed for environmental decision support. It generates a synthetic population of individuals and defines the mobility of each individual in the city through an activity-based approach of travel demand. The model then spatializes road traffic by taking into account congestion on the road network. It also includes a module that estimates the energy demand of the territory by calculating the unit energy consumption of households and the commercial–institutional sector. Finally, the emissions associated with all the modeled activities are calculated using the COPERT emission factors for traffic and the European Environmental Agency (EEA) methodology for heating-related combustion. The comparison of emissions with AIRPARIF's regional inventory shows discrepancies that are consistent with differences in assumptions and input data, mainly in the sense of underestimation. The methodological choices and the potential ways of improvement, including the refinement of traffic congestion modeling and of the transport of goods, are discussed.

Detection of vehicle wheels from images using a pseudo‐wavelet filter for analysis of congested traffic

There is potential for significant savings if the safety of existing bridges can be more accurately assessed. For long-span bridges, congestion is the governing traffic load condition. The current methods of simulating congestion make assumptions about the axle-to-axle gaps maintained between vehicles. There is potential for improvement in congestion models if accurate data on axle-to-axle gaps can be obtained. In this study, the use of a camera to collect this information is put forward. A new image processing technique is proposed to detect wheels in variable light conditions. The method is based on a pseudo-wavelet filter that amplifies circles, in conjunction with an algorithm that weights features in the image according to their circularity. This new approach is compared with the Hough transform, template matching and the deformable part-based model (DPM) methods previously developed. In a sample set of 80 images, 96.9% of wheels are detected, considerably more than with the Hough transform and template matching methods. It also provides the same level of accuracy as DPM without requiring a training process.

The antiexudative action of the plant extract “Venosten”

Vein diseases remain one of the most urgent unsolved issues of modern medicine. Development of new, original herbal medicines for the treatment of varicose veins is a topical substantiated direction in the pharmaceutical technology.Aim. To study the effectiveness of the use of a new thick extract “Venosten” for correction of disorders in rats under venous congestion and edema.Materials and methods. Venous stasis and swelling in rats were caused by occlusion of the tail. At the base of the tail the ligature was applied with a load in the form of a 200 g metal weight for 3 hours. The venotonic activity of the thick extract “Venosten” was studied in the doses of 25 mg/kg, 50 mg/kg and 100 mg/kg. Development of swelling was assessed by the tail volume increase, which was measured in dynamics within 3 hours after ligation, and in 1, 2 and 24 hours after removal of the ligature. The tail volume was measured using a mechanical oncometer.Results. The thick extract “Venosten” showed a pronounced dose-dependent anti-exudative activity. The extract in the dose of 25 mg/kg exhibits a moderate efficacy, and its total anti-edema activity was 16.5 %. The thick extract “Venosten” in the dose of 50 mg/kg from the first hour after the ligature application significantly reduced development, and the average anti-exudative effect was expressed and equaled 39 %. The most pronounced anti-edema effect was expressed in the extract in the dose of 100 mg/kg. In 3 hours from the time of ligation the volume of the tail increased only by 12 %. After removing the ligature the volume of the tail continued to grow, and in 1 hour after the removal of the ligature it began to decrease compared to the value at the beginning of the experiment.Conclusions. The data obtained indicate the pronounced anti-edema activity of the thick extract “Venosten” in the dose of 100 mg/kg on the model of venous congestion in rats.

Parallel Metric Tree Embedding Based on an Algebraic View on Moore-Bellman-Ford

A metric tree embedding of expected stretch α ≥ 1 maps a weighted n -node graph G = ( V , E , ω) to a weighted tree T = ( V T , E T , ω T ) with V ⊑ V T such that, for all v , w ∈ V , dist( v , w , G ) ≤ dist( v , w , T ), and E[dist( v , w , T )] ≤ α dist( v , w , G ). Such embeddings are highly useful for designing fast approximation algorithms as many hard problems are easy to solve on tree instances. However, to date, the best parallel polylog n )-depth algorithm that achieves an asymptotically optimal expected stretch of α ∈ O(log n ) requires Ω ( n 2 ) work and a metric as input. In this article, we show how to achieve the same guarantees using polylog n depth and Õ( m 1+ε ) work, where m = | E | and ε &gt; 0 is an arbitrarily small constant. Moreover, one may further reduce the work to Õ( m + n 1+ε ) at the expense of increasing the expected stretch to O(ε −1 log n ). Our main tool in deriving these parallel algorithms is an algebraic characterization of a generalization of the classic Moore-Bellman-Ford algorithm. We consider this framework, which subsumes a variety of previous “Moore-Bellman-Ford-like” algorithms, to be of independent interest and discuss it in depth. In our tree embedding algorithm, we leverage it to provide efficient query access to an approximate metric that allows sampling the tree using polylog n depth and Õ( m ) work. We illustrate the generality and versatility of our techniques by various examples and a number of additional results. Specifically, we (1) improve the state of the art for determining metric tree embeddings in the Congest model, (2) determine a (1 + εˆ)-approximate metric regarding the distances in a graph G in polylogarithmic depth and Õ( n ( m + n 1 + ε )) work, and (3) improve upon the state of the art regarding the k -median and the buy-at-bulk network design problems.

Novel design for bifurcation control in a delayed fractional dual congestion model

This letter puts forward an ingenious feedback control method with parametric delay to manipulate bifurcation control for a delayed fractional dual congestion model. By employing time delay as a bifurcation parameter, the local dynamics involving stability and Hopf bifurcation is examined. The control efforts can be realized with or without time delay in the strength of feedback control. It suggests that the stability performance is consumedly elevated by exploiting the parametric delay feedback controller, yet Hopf bifurcation engenders ahead of time in the event of the absence of the controller. Moreover, the impact of the order or linear feedback gain on the bifurcation point is numerically discussed via aborative calculation. Numerical simulations are eventually actualized to corroborate the proposed scheme.

Efficient Algorithms for Constructing Very Sparse Spanners and Emulators

Miller et al. [48] devised a distributed 1 algorithm in the CONGEST model that, given a parameter k = 1,2,…, constructs an O ( k )-spanner of an input unweighted n -vertex graph with O ( n 1+1/ k ) expected edges in O ( k ) rounds of communication. In this article, we improve the result of Reference [48] by showing a k -round distributed algorithm in the same model that constructs a (2 k −1)-spanner with O ( n 1+1/ k }/ϵ) edges, with probability 1−ϵ for any ϵ&gt;0. Moreover, when k =ω(log n ), our algorithm produces (still in k rounds) ultra-sparse spanners, i.e., spanners of size n (1+ o (1)), with probability 1− o (1). To our knowledge, this is the first distributed algorithm in the CONGEST or in the PRAM models that constructs spanners or skeletons (i.e., connected spanning subgraphs) that are sparse. Our algorithm can also be implemented in linear time in the standard centralized model, and for large k , it provides spanners that are sparser than any other spanner given by a known (near-)linear time algorithm. We also devise improved bounds (and algorithms realizing these bounds) for (1+ϵ, β)-spanners and emulators. In particular, we show that for any unweighted n -vertex graph and any ϵ &gt; 0, there exists a (1+ ϵ, (log log n / ϵ) log log n )-emulator with O ( n ) edges. All previous constructions of (1+ϵ, β)-spanners and emulators employ a superlinear number of edges for all choices of parameters. Finally, we provide some applications of our results to approximate shortest paths’ computation in unweighted graphs.

Pathophysiological and molecular mechanisms involved in renal congestion in a novel rat model

Increased central venous pressure in congestive heart failure causes renal dysfunction; however, the underlying mechanisms are unclear. We created a rat renal congestion model and investigated the effect of renal congestion on hemodynamics and molecular mechanisms. The inferior vena cava (IVC) between the renal veins was ligated by suture in male Sprague-Dawley rats to increase upstream IVC pressure and induce congestion in the left kidney only. Left kidney congestion reduced renal blood flow, glomerular filtration rate, and increased renal interstitial hydrostatic pressure. Tubulointerstitial and glomerular injury and medullary thick ascending limb hypoxia were observed only in the congestive kidneys. Molecules related to extracellular matrix expansion, tubular injury, and focal adhesion were upregulated in microarray analysis. Renal decapsulation ameliorated the tubulointerstitial injury. Electron microscopy captured pericyte detachment in the congestive kidneys. Transgelin and platelet-derived growth factor receptors, as indicators of pericyte-myofibroblast transition, were upregulated in the pericytes and the adjacent interstitium. With the compression of the peritubular capillaries and tubules, hypoxia and physical stress induce pericyte detachment, which could result in extracellular matrix expansion and tubular injury in renal congestion.

Undesirable and desirable energy congestion measurements for regional coal-fired power generation industry in China

The blind expansion and increasing carbon emissions of the coal-fired power generation industry in China have attracted wide attention at home and abroad. To detect the technical ineffectiveness in the coal-fired power generation industry and the effects of carbon emission reductions, this study developed energy congestion models using data envelopment analysis (DEA). Energy congestion is classified into undesirable energy congestion (UEC) and desirable energy congestion (DEC) under natural disposability and managerial disposability. The UEC and DEC models were used to identify energy congestion, measure the amounts of UEC and DEC, and analyze the sources of inefficiency for regional coal-fired generation industry in China from 2004 to 2013. Our empirical analysis revealed: i) The UEC of coal-fired generation industry has occurred in many regions, most of which are less-developed areas. This indicates that energy is wasted in coal-fired generation industry due to congestion inefficiency. ii) DEC has occurred in a few regions and did not occur in 2013. These provinces where DEC occurred may have a high potential for eco-technology innovation. The method of energy congestion measurement proposed in this study and the research conclusion have reference effect on regional energy conservation and eco-technology innovation.

Analysis of a Congestion Model in a Wireless Access Network with One Bottleneck Router and N TCP Flows

Analysis of a Congestion Model in a Wireless Access Network with One Bottleneck Router and N TCP Flows

Abstract P127: Pericyte Detachment is Involved in Renal Congestion in a Novel Rat Model

Increased central venous pressure in congestive heart failure is responsible for renal dysfunction; however, the underlying mechanisms are unclear. We hypothesized that renal interstitial hydrostatic pressure (RIHP) and expansion pressures of the vasa recta are responsible for pericyte detachment resulting renal congestion-mediated fibrosis. We created a novel rat renal congestion model and investigated the effect of renal congestion on hemodynamics and its molecular mechanisms. The inferior vena cava (IVC) between the renal veins was ligated by suture in male Sprague-Dawley rats to increase upstream IVC pressure and induce congestion in the left kidney only. Left kidney congestion reduced renal blood flow in cortex (33.6%, 28.3 to 16.0 mL/min) and in medulla (41.8%, 11.9 to 6.9 mL/min) and glomerular filtration rate (1.16 to 0.20 mL/min/kg BW), and increased RIHP (12.6 to 17.6 mm Hg). Hypoxia was observed in the medullary thick ascending limb of Henle, only in the congestive kidneys. Tubulointerstitial injury, podocyte injury, albuminuria, and reduced creatinine clearance were observed in the congestive kidneys. Molecules related to extracellular matrix expansion, tubular injury, and focal adhesion were upregulated in microarray analysis. Renal decapsulation ameliorated the tubulointerstitial injury (mRNA expression of Kim1 15.3 to 4.3 A.U., αSma 5.3 to 2.8 A.U.). Electron microscopy captured pericyte detachment in the congestive kidneys. Transgelin and platelet-derived growth factor receptors (PDGFRs), as indicators of pericyte-myofibroblast transition, were upregulated in the pericytes and the adjacent interstitium. Imatinib, a PDGFR inhibitor, ameliorated the interstitial injury. Our results reveal a novel mechanism of worsening renal function associated with congestive heart failure, and provide a new therapeutic strategy based on a better understanding of the pericyte-myofibroblast transition.

A Novel Framework to Control and Optimize the Traffic Congestion Issue in VANET

In the recent times due to the increase of vehicular nodes in a vehicular communication network, there is a need of developing efficient systems in order to optimize the vehicular traffic congestion issues in urban areas. The current research trends shows that most of the conventional studies focused on developing fuzzy inference systems based vehicular traffic congestion model which has gained lots of attention on detecting and minimizing the congestion levels.We have proposed a new approach towards detection and controlling of traffic congestion in VANET. The proposed system utilizes the communication channels very efficiently and irrespective of any kind of overload. This proposed system aims to introduce a novel framework for identifying traffic jam on Vehicular Ad-hoc Networks. In order to detect and minimize the level of congestion our approach will use a fuzzy logic based approach to notify the drivers about available routes during the traffic congestion. An experimental prototype will be set up to enable the graphical simulation.