Congestion Reduction Research Articles

Scaling up urban infrastructure for physical activity in the COVID-19 pandemic and beyond

Scaling up urban infrastructure for physical activity in the COVID-19 pandemic and beyond

The role of bike sharing stations in the perception of public spaces: A stated preferences analysis

The pervasiveness of bike sharing schemes around the world has the potential to bring important benefits in terms of public health and reduction of congestion and emissions. However, there can be negative externalities associated to these systems, especially in terms of misuse and degradation of public spaces. This paper explores how the presence of different shared bicycle systems and their stations affect peoplés perceptions of public spaces and neighbourhoods. For this, a stated preferences experiment was created and applied in Santiago de Chile, depicting two main scenarios (downtown and residential) with various configurations of public bicycle stations (dock-based and dockless), along other cycling facilities on a street. Survey results were used to estimate a choice model, measuring the impact of the scenario attributes on the probability of being chosen as a preferred public space. Attitudes about bikesharing, the environment and mobility in general were also measured and used to estimate latent variables and their role in public space perception. Results show bike sharing stations are overall positively perceived in terms of their capacity to improve a neighbourhood’s image, safety and accessibility, although this is more likely in compact urban contexts and for users of bikesharing. Disorganized (dockless) bicycles left on sidewalks are perceived negatively, although not enough to make individuals prefer a situation without public bicycles. The previous findings indicate that bike sharing schemes could have positive effects on the image of neighbourhoods by making them look more attractive and modern.

Loop Algorithms for Ductility Analysis of Column Reinforced Steel with Yield Strength Above 500 MPA

There are many benefits to the use of high-strength reinforcement (above 500 MPa) in reinforced concrete buildings. The advantages of using high-strength reinforcement are reduction steel volume and dimension, reduced construction time, reduction in reinforcement congestion, as well as savings in materials and worker cost. Meanwhile, the investigation of ductility of reinforced concrete element with high-strength reinforcement to resist earthquake effects under current design procedure is needed. In the current standard, ACI 318-71, The maximum specified yield strength was restricted to 60 Ksi (413 MPa) for reinforcement in special seismic system. There were also no ASTM standard specifications for reinforcement with yield strength above 500 MPa. In the design of seismic resisting structures, the analysis of curavture ductility and flexural overstrength factor is of important consideration in order to avoid brittle failure. This paper attempts to anaylze the ductility and re-evaluate the flexural overstrength factor of reinforced concrete column. The tensile tests of steel reinforcement with yield strength above 500 MPa generates stress-strain curve. An idealisations for the monotonic stress-strain curve proposed by mander was adopted in this study. Whereas in this numerical study of confined concrete columns, the behavior of concrete cored is modeled by the stress-strain relationship of confined concrete proposed by Kappos-Konstantinidis. This stress strain model was used for the momen, curvature, ductility, and flexural overstrength factor analysis.

Impact of COVID-19 Social Distancing Policies on Traffic Congestion, Mobility, and NO2 Pollution

Lockdowns implemented during the COVID-19 pandemic were utilized to evaluate the associations between “social distancing policies” (SDPs), traffic congestion, mobility, and NO2 air pollution. Spatiotemporal linear mixed models were used on city-day data from 22 US cities to estimate the associations between SDPs, traffic congestion and mobility. Autoregressive integrated moving average models with Fourier terms were then used on historical data to forecast expected 2020 NO2. Time series models were subsequently employed to measure how much reductions in local traffic congestion were associated with lower-than-forecasted 2020 NO2. Finally, the equity of NO2 pollution was assessed with community-level sociodemographics. When cities’ most stringent SDPs were implemented, they observed a 23.47 (95% CI: 18.82–28.12) percent reduction in average daily congestion and a 13.48 (95% CI: 10.36–16.59) percent decrease in average daily mobility compared to unrestricted days. For each standard deviation (8.38%) reduction in local daily congestion, average daily NO2 decreased by 1.37 (95% CI: 1.24–1.51) parts per billion relative to its forecasted value. Citizenship, education, and race were associated with elevated absolute NO2 pollution levels but were not detectibly associated with reductions in 2020 NO2 relative to its forecasted value. This illustrates the immediate behavioral and environmental impacts of local SDPs during the COVID-19 pandemic.

Security Enhancement in Smart Vehicle Using Blockchain-based Architectural Framework

The concept of interconnecting smart vehicles and advancements in automotive automation leads to beneficial outcomes, such as a reduction in road fatalities and congestion. However, including a chain of automation in the attack surface will expand the attack surface and expose the security of automobiles to malicious infiltration. The proposed methodology provides access to specific users while restricting the third party requests. Moreover, it also makes use of data exchange that takes place between the roadside units and vehicle to track the vehicle status without compromising the in-vehicle network. To ensure a valid and authentic communication, vehicles with a proper and verifiable record will only be allowed to exchange messages in the blockchain network. Using qualitative arguments, we have identified that the proposed work is resilient to identified attacks. Similarly, quantitative experimentation indicates that this methodology shows a storage size compatibility and suitable response time in realistic scenarios. Simulation results indicate that, the proposed work shows positive results to secure vehicular networks, vehicular forensics and trust management.

ComplexTrans – Global Rail-Road Transportation System: The Best Way Ahead for Railways and Roads Is Coherent Cooperation, Not the Competition

Land transport can no longer meet the requirements. Crowded motorways and cities, dangerous emissions, ubiquitous traffic accidents, delays, expensive railways. Solutions are being sought to transfer a large part of passenger and especially freight transport to rail, and efforts are moving towards electromobility, car-sharing, 5G-connectivity, autonomous driving, MaaS-coordinated transport or Hyperloop-type solutions. However, all these solutions have additional challenges and limitations. Solutions are not being searched where they really exist - in the mutual adaptation of road and rail vehicles and their deep cooperation. The ComplexTrans project shows that simply adapting the dimensions and functions of road and rail vehicles can eliminate or significantly reduce all the problems of existing land transport. The main features of the ComplexTrans system are sufficient parking spaces, reduction of road congestions, cheap e-vehicles with unlimited range and increased utility value, cheap and simple charging infrastructure, 'autonomous' ride, easy cooperation of passenger and freight rail transport, railway self-financing, transferring big portion of transport from road and air to rail, covid protection and many others.

Assignment of Freight Truck Shipment on the U.S. Highway Network

With the ever-increasing demand for freight movements, nationwide freight shipments between geographical regions by freight trucks need to be investigated since they comprise the largest share of total freight movements in the United States. To this end, the procedures for freight truck shipment demand network assignment on the entire U.S. highway network considering congestion effect are discussed, and the results are explained in detail, with visual illustrations. A fundamental traffic assignment model with a convex combinations algorithm is proposed to solve the nationwide freight truck shipment assignment problem under the user equilibrium principle. A link cost function is modified, considering the traffic volume that already exists on U.S. highways. A case study is conducted using big data including the entire U.S. highway network and freight shipment information in 2007. Total and average freight shipment costs for both truck and rail transportation for a specific origin–destination pair in the database are computed to compare the characteristics of these two major freight transportation modes in the United States. Application of the proposed model could be possible to address many other related problems, such as improvement of highway infrastructure, and reductions in traffic congestion and vehicle emissions.

Forming coordination group for coordinated traffic congestion management schemes

It has been well known that properly coordinating travelers’ route choices will help mitigate urban traffic congestion. Accordingly, coordinated routing mechanisms (CRMs), functioned as coordinated network congestion management schemes, have been developed in recent years. They often employ game theory models to strategically coordinate the route decisions of a group of travelers en route with the aim to reduce network traffic congestion. However, existing studies do not provide the solution about how to form the traveler groups, such as who and how many travelers the CRMs should involve. This issue may jeopardize the efficiency and scalability of the CRMs in practical applications. To make up this gap, this study seeks to develop the clustering aided network modeling approaches to form the coordination groups (CGs), which have the proper members and sizes for supporting the merits of the congestion management schemes. Specifically, we define coordination potential as an index to indicate the potential benefit for coordinating travelers’ route decisions on network congestion reduction. Then we develop rigorous approaches to understand the mathematical features and further quantify the coordination potential between two travelers, and among multiple travelers. Built upon that, we form the CGs through a well-designed adaptive centroid-based clustering algorithm (ACCA). It secures a local optimal clustering solution, balancing the intra-cluster and inter-cluster CP, so that we can ensure a small system performance loss as we implement a CRM on each CG. The efficiency of the CG formation approach is evaluated by the CG-CRM scheme, which partitions the travelers into multiple CGs and independently coordinates the travelers’ route choices in each CG by a CRM. The numerical experiments built upon both Sioux Falls and Hardee city networks confirm the efficiency and effectiveness of the CG formation approach. Mainly, the CG-CRM outperforms the independent best response routing mechanism in system performance. As compared to the CRM working on a single group involving all travelers, the CG-CRM requires significantly less computation load with a minor compromise on the system performance. This merit becomes more apparent under high penetration and congested traffic condition. Therefore, we claim that the CG formation approach will significantly help the implementation of the coordinated congestion mitigation schemes in practice.

KAJIAN PENGARUH PEMBANGUNAN JALAN TOL SEMARANG - DEMAK TERHADAP KINERJA JALAN RAYA KALIGAWE

The increasing movement causes traffic jams. One of the congestion occurred on Jalan Raya Kaligawe, Semarang. Jalan Raya Kaligawe is a road located close to the coast. So that when the sea water experiences high tide, the road will be inundated by tidal floods. This condition results in very high traffic jams every year. To deal with congestion and overcome the problem of sea water flooding, the government plans to build the Semarang - Demak Toll Road. With the existence of this Toll Road, it is hoped that congestion on the Kaligawe Road will be reduced. But the reduction in congestion needs research. So the researchers conducted a study on the effect of the construction of the Semarang - Demak Toll Road on the performance of the Kaligawe Highway. The purpose of this study, among others, is to determine the level of service, prediction of the diversion of traffic loads and predictions of increasing work on Jalan Raya Kaligawe. This study uses three stages in the research method, namely the identification stage, the data collection and processing stage, and the analysis and conclusion stages. The analysis technique used in this research is the formulation of traffic loading around the location due to development, both at the time and post, added with base traffic to get a real loading on the area of influence with the construction of the Semarang - Demak toll road.

Salmonella Enteritidis foodborne infection induces altered placental morphometrics in the murine model

IntroductionSalmonella foodborne disease during pregnancy causes a significant fetal loss in domestic livestock and preterm birth, chorioamnionitis and miscarriage in humans. These complications could be associated with alterations in placental structure. This study was aimed to determine how a low dose of Salmonella Enteritidis during late gestation affects placental histomorphometric in mice. MethodsWe used a self-limiting enterocolitis murine model. BALB/c pregnant animals received a low dose of Salmonella Enteritidis (3–4 x 102 CFU/mouse) on gestational day (GD) 15. At day 3 post infection bacterial loads, serum cytokines expression and placental histomorphometrics parameters were analyzed. ResultsWe found that a sub-lethal infection with Salmonella induced a significant drop in fetal weight -to-placental weight-ratio and an increase in the placental coefficient. After bacterial inoculation maternal organs were colonized, inducing placental morphometric alterations, including increased placental thickness, reduced surface area, and diminished major and minor diameters. Also, foci of necrosis accompanied by acute leukocyte infiltration in decidual zone, reduction of vascular spaces and vascular congestion in labyrinth zone, were also evident in placentas from infected females on GD 18. Our data shows that placentas from infected mothers are phenotypically different from control ones. Furthermore, expression of IFN-gamma and IL-6 was up regulated in response to Salmonella in maternal serum. DiscussionOur findings demonstrate that a low dose of Salmonella during late gestation alters the placental morphometry leading to negative consequences on pregnancy outcome such as significant reduction in fetal body weight.

HADES: A Multi-Agent Platform to Reduce Congestion Anchoring Based on Temporal Coordination of Vessel Arrivals—Application to the Multi-Client Liquid Bulk Terminal in the Port of Cartagena (Spain)

Ports are key factors in international trade, and new port terminals are quite costly and time consuming to build. Therefore, it is necessary to optimize existing infrastructure to achieve sustainability in logistics. This problem is more complex in multi-client port terminals, where quay infrastructure is shared among terminal operators who often have conflicting interests. Moreover, the berth allocation problem in liquid bulk terminals implies demanding restrictions due to the reduced flexibility in berth allocation for these types of goods. In this context, this paper presents HADES, a multi-agent platform, and the experience of its pilot use in the Port of Cartagena. HADES is a software platform where agents involved in vessel arrivals share meaningful but limited information. This is done to alleviate potential congestion in multi-client liquid bulk terminals, promoting a consensus where overall congestion anchoring is reduced. A study is presented using a mixed integer linear program (MILP) optimization model to analyze the maximum theoretical reduction in congestion anchoring, depending on the flexibility of vessel arrival time changes. Results show that 6 h of flexibility is enough to reduce congestion anchoring by half, and 24 h reduces it to negligible values. This confirms the utility of HADES, which is also briefly described.

Long-Term Safety Analysis of Hard Shoulder Running on Freeways in Germany

On freeways with high traffic demand, hard shoulder running (HSR) can be an effective traffic management measure to increase the capacity by providing an additional travel lane during peak hours. While the positive effects of HSR on traffic flow quality were documented in several studies, the implications of HSR on road safety are more ambiguous. This paper presents results of a study in which accident data for seven freeway sections with HSR on freeways in Germany were analyzed over a long period of 13 years. All investigated sections are equipped with variable speed limits. The evaluation of crash frequencies on the investigated freeway sections revealed a high safety level. By combining crash data and traffic data it is shown that crash occurrence depends on the prevailing traffic conditions, with congestion being the most critical traffic state in relation to safety. Therefore, safety improvements upstream of HSR segments can be related to the improved traffic flow and the reduction of congestion. In conclusion, the results of the investigation provide evidence that the implementation of HSR can improve road safety if state-of-the-art traffic control technology is applied and congestion can be relieved.

Enabling Technologies for Urban Smart Mobility: Recent Trends, Opportunities and Challenges.

The increasing population across the globe makes it essential to link smart and sustainable city planning with the logistics of transporting people and goods, which will significantly contribute to how societies will face mobility in the coming years. The concept of smart mobility emerged with the popularity of smart cities and is aligned with the sustainable development goals defined by the United Nations. A reduction in traffic congestion and new route optimizations with reduced ecological footprint are some of the essential factors of smart mobility; however, other aspects must also be taken into account, such as the promotion of active mobility and inclusive mobility, encouraging the use of other types of environmentally friendly fuels and engagement with citizens. The Internet of Things (IoT), Artificial Intelligence (AI), Blockchain and Big Data technology will serve as the main entry points and fundamental pillars to promote the rise of new innovative solutions that will change the current paradigm for cities and their citizens. Mobility-as-a-service, traffic flow optimization, the optimization of logistics and autonomous vehicles are some of the services and applications that will encompass several changes in the coming years with the transition of existing cities into smart cities. This paper provides an extensive review of the current trends and solutions presented in the scope of smart mobility and enabling technologies that support it. An overview of how smart mobility fits into smart cities is provided by characterizing its main attributes and the key benefits of using smart mobility in a smart city ecosystem. Further, this paper highlights other various opportunities and challenges related to smart mobility. Lastly, the major services and applications that are expected to arise in the coming years within smart mobility are explored with the prospective future trends and scope.

Simulation-optimization of automated material handling systems in a healthcare facility

Automated material handling systems are used in healthcare facilities to optimize material flow, minimize workforce requirements, reduce risk of contamination, and reduce work injuries. This paper develops a case study using data from Greenville Memorial Hospital (GMH) in South Carolina, USA. The case study is focused on the delivery of surgical case carts to operating rooms at GMH via Automated Guided Vehicles (AGVs). This study proposes a framework that integrates data analysis with system simulation and optimization. The study addresses the following research questions: (1) Redesign of the pathways: Do performance measures, such as travel time and task completion time, improve after a redesign of AGV pathways? (2) Operational fleet sizing: Do performance measures, such as travel time and task completion time, improve when the number of AGVs used daily is controlled by the volume of surgical cases? If this is true, then how many AGVs should be used daily? To address research question (1), we compare two AGV pathway designs via an extensive sensitivity analysis. To address research question (2), we use a simulation-optimization model to evaluate the performance of the system for different fleet sizes. Finally, we conduct a pilot study at GMH to validate the results of our analysis. This study indicates that the proposed solution, which uses a smaller fleet of AGVs than currently used at GMH, leads to significant reductions in congestion and travel times, and increased utilization of AGVs.

Promoting public transport as a strategy to reduce GHG emissions from private vehicles in Kuwait

Traffic congestion is one of the most important problems that faces metropolises despite of the measures being taken to mitigate and reduce such problem. Traffic congestion in Kuwait requires a rapid solution, especially in Kuwait City. Public transportation can decrease the number of private vehicles to ease the traffic congestion, provide a good impact on the environment, and enhance the cost-effectiveness, reliability, and accessibility of the road network. This research encourages the use of public transportation for congestion reduction. All needed data were collected from different sources. They were used to simulate the future network condition in terms of reducing traffic congestion, fuel consumption, and gas emissions. The obtained data were processed using synchro software. The findings showed a reduction in the congestion by about 45% in some streets. The environmental impact was enhanced with a noticeable level of reduction in the gas emissions. The fuel consumption was reduced to 46% after the improved data. The consumer surplus was 7848.32 KD while the social welfare was 57258.6 KD for this study.

Urban consolidation centers: Impact analysis by stakeholder

An Urban Consolidation Center is a city logistics solution that contributes to reducing the negative effects of transportation activities in urban areas, but few projects have been implemented fully and financial sustainability is commonly mentioned as a constraint to their implementation. The objective of this research is two-fold: to present a methodology to include socio-environmental impact monetization in the economic evaluation of urban consolidation center projects and to discuss the result of UCC project economic evaluations considering foundations of Welfare Economics. For this purpose, the impacts for each stakeholder were identified, their monetization was incorporated in the analysis and the results were discussed in light of the Kaldor-Hicks criterion. Two Brazilian cases are used to apply the proposed methodology. The results show that when socio-environmental impacts, such as a reduction in traffic congestion and pollution emissions, are incorporated into the economic evaluation, implementation is justified for cities with high levels of traffic congestion. This study might improve the future analysis of urban consolidation center projects by performing a more comprehensive economic evaluation. Notably, it includes social, environmental and monetary benefits for different stakeholders, and is relevant for practitioners and public administrators.

A Back-of-Queue Model of a Signal-Controlled Intersection Approach Developed Based on Analysis of Vehicle Driver Behavior

In smart cities, it is expected that transport, communication as well as the movement of people and goods will take place in the shortest possible time while maintaining a high level of safety. In recent years, due to the significant increase in the number of passengers and vehicles on the road and the capacity limitations of transport networks, it has become necessary to use new technologies for intelligent control and traffic management. Intelligent transport systems use advanced technologies in the field of data gathering, information processing, and traffic control to meet current transport needs. To be able to effectively control and manage road traffic, it is necessary to have reliable mathematical models that allow for a faithful representation of the real traffic conditions. Models of this type are usually the basis of complex algorithms used in practice in road traffic control. The application of appropriate models reflecting the behavior of road users contributes to the reduction of congestion, the vehicles travel time on the transport network, fuel consumption and the emissions, which in turn support broadly understood energy savings. The article proposes a model that allows for the estimation of the maximum queue size at the signal-controlled intersection approach (so-called: maximum back-of-queue). This model takes into account the most important traffic characteristics of the vehicles forming this queue. The verification allowed for the conclusion that the proposed model is characterized by high compliance with the actual traffic and road conditions at the intersections with signal controllers located in built-up areas in Poland. The obtained compliance confirms the possibility of using the model for practical applications in calculating the maximum back-of-queue at signal-controlled intersections located in built-up areas in Poland.

Available Transfer Capability Enhancement by FACTS Devices Using Metaheuristic Evolutionary Particle Swarm Optimization (MEEPSO) Technique

Energy power flows are an important factor to be calculated and, thus, are needed to be enhanced in an electrical generation system. It is very necessary to optimally locate the Flexible Alternating Current Transmission Systems (FACTS) devices and improve the Available Transfer Capability (ATC) of the power transmission lines. It relieves the congestion of the system and increases the flow of power. This research study has been accomplished in two stages: optimization of location of FACTS device by the novel Sensitivity and Power loss-based Congestion Reduction (SPCR) method and the calculation of ATC using the proposed Metaheuristic Evolutionary Particle Swarm Optimization (MEEPSO) technique. The Thyristor Controlled Series Capacitor (TCSC) is used as a FACTS device to control the reactance of power transmission line. The effectiveness of the proposed methods is validated, utilizing the six bus as well as 30 bus system. The acquired outcomes are contrasted with conventional ACPTDF and DCPTDF procedures. These values are determined with the assistance of MATLAB version 2017 on the Intel Core i5 framework by taking two-sided exchanges and they are contrasted and values determined with the assistance of Power World Simulator (PWS) programming.

Proteomic and Mechanistic Analysis of Spironolactone in Patients at Risk for HF

ObjectivesThis study sought to further understand the mechanisms underlying effect of spironolactone and assessed its impact on multiple plasma protein biomarkers and their respective underlying biologic pathways. BackgroundIn addition to their beneficial effects in established heart failure (HF), mineralocorticoid receptor antagonists may act upstream on mechanisms, preventing incident HF. In people at risk for developing HF, the HOMAGE (Heart OMics in AGEing) trial showed that spironolactone treatment could provide antifibrotic and antiremodeling effects, potentially slowing the progression to HF. MethodsBaseline, 1-month, and 9-month (or last visit) plasma samples of HOMAGE participants were measured for protein biomarkers (n = 276) by using Olink Proseek-Multiplex cardiovascular and inflammation panels (Olink, Uppsala, Sweden). The effect of spironolactone on biomarkers was assessed by analysis of covariance and explored by knowledge-based network analysis. ResultsA total of 527 participants were enrolled; 265 were randomized to spironolactone (25 to 50 mg/day) and 262 to standard care (“control”). The median (interquartile range) age was 73 years (69 to 79 years), and 26% were female. Spironolactone reduced biomarkers of collagen metabolism (e.g., COL1A1, MMP-2); brain natriuretic peptide; and biomarkers related to metabolic processes (e.g., PAPPA), inflammation, and thrombosis (e.g., IL17A, VEGF, and urokinase). Spironolactone increased biomarkers that reflect the blockade of the mineralocorticoid receptor (e.g., renin) and increased the levels of adipokines involved in the anti-inflammatory response (e.g., RARRES2) and biomarkers of hemostasis maintenance (e.g., tPA, UPAR), myelosuppressive activity (e.g., CCL16), insulin suppression (e.g., RETN), and inflammatory regulation (e.g., IL-12B). ConclusionsProteomic analyses suggest that spironolactone exerts pleiotropic effects including reduction in fibrosis, inflammation, thrombosis, congestion, and vascular function improvement, all of which may mediate cardiovascular protective effects, potentially slowing progression toward heart failure. (HOMAGE [Bioprofiling Response to Mineralocorticoid Receptor Antagonists for the Prevention of Heart Failure]; NCT02556450)

Evaluating car-sharing switching rates from traditional transport means through logit models and Random Forest classifiers

ABSTRACT Positive impacts of car-sharing, such as reductions in car ownership, congestion, vehicle-miles-traveled and greenhouse gas emissions, have been extensively analyzed. However, these benefits are not fully effective if car-sharing subtracts travel demand from existing sustainable modes. This paper evaluates substitution rates of car-sharing against private cars and public transport using a Random Forest classifier and Binomial Logit model. The models were calibrated and validated using a stated-preference travel survey and applied to a revealed-preference survey, both administered to a representative sample of the population living in Turin (Italy). Results of the two models show that the predictive power of both models is comparable, albeit the Logit model tends to estimate predictions with a higher reliability and the Random Forest model produces higher positive switches towards car-sharing. However, results from both models suggest that the substitution rate of private cars is, on average, almost five times that of public transport.