Congestion Level Research Articles

CLINICO-MYCOLOGICAL STUDY OF TINEA CAPITIS

Dermatophytes from the genera Trichophyton and Microsporum cause tinea capitis, a supercial fungal infection of the scalp and scalp hair. The fungi that cause the condition might change over time and space. Tinea capitis mostly affects youngsters, though it can sometimes affect adults. Children between the ages of 3 and 14 are the ones who are most likely to develop it . The lack of fatty acids in sebum, which have a fungi-static effect, has been linked to the increased prevalence in prepubertal children. With poor personal hygiene, congestion, and low socioeconomic level, transmission is exacerbated . The species may evolve over time in any location, particularly as new organisms are brought in via immigration. In order to identify the numerous etiological agents, different clinical kinds, research the epidemiological features, and establish the clinico-mycological association of tinea capitis, a study was carried out in our hospital .

Packet rank-aware active queue management for programmable flow scheduling

Flow scheduling is crucial in improving network Quality of Service (QoS). According to different optimization goals, many scheduling algorithms (e.g., STFQ, pFabric, SRPT, WFQ) have emerged in network. However, these scheduling algorithms are bound with hardware, which are only applicable to fixed network scenarios. Push-In First-Out (PIFO) queues are proposed as a queue abstraction to support programmable packet scheduling, but implementing them in hardware is difficult. We present a general framework named PR-AQM, which uses limited number of FIFO queues to approximate PIFO behavior. The core idea of PR-AQM is to perform Active Queue Management (AQM) on programmable data plane by capturing packet rank distribution and queue congestion level in real time. Specifically, PR-AQM can dynamically adjust the mapping between packet ranks and queues according to the delay status of different priority queues, thus efficiently achieving priority scheduling of packets. We carry out extensive simulations and implement PR-AQM prototype in Tofino switches to evaluate the performance of PR-AQM. Experimental results show that compared with state-of-the-art algorithms, PR-AQM can adapt well to different scheduling algorithms, and achieve better performance by reducing the average flow completion time for short flows up to 45%.

The concentration of edge betweenness in the evolution of planar graphs and street networks

AbstractThe centrality measures of the nodes and edges of the street networks are related to various urban phenomena. In particular, betweenness centrality correlates with the spatial distribution of economic activities, the levels of congestion, and the structural changes in cities. In this work, we study how betweenness tends to concentrate in a small set of edges and develop a model to analyse this concentration throughout the growth of graphs. We show that random planar graphs tend to betweenness concentration as the number of nodes increases. The evolution of Paris and Tijuana street networks shows the same behaviour but at a higher rate. A set of 300 street networks worldwide follows a similar relationship between the number of nodes and the betweenness concentration. We find a significant correlation between congestion ranks and betweenness concentration.

Using Reputation Scores to Foster Car-Sharing Activities

In the near future, the growth of personal mobility is expected to continue all over the world and to cause impacts such as increased levels of traffic congestion and worsened quality of life, mainly in highly populated urban areas. Alternative solutions for individual mobility have been promoted to dissuade people from using private cars. Particularly, renting private vehicles scarcely used by their owners would result in several benefits, including environmental ones, and traffic reduction. This type of solution, based on the willingness of individuals to rent their own vehicles, is called Peer-to-Peer Car-Sharing (P2P-CS). This study proposes a methodological approach focused on the adoption of both a reputation system and blockchain technology to support P2P-CS activities. Reputation scores are introduced to meet CS actors’ expectations of dealing with trusted partners, by allowing both access to service and the opportunity to customize CS fares, while the blockchain makes reputation scores publicly accessible and unchangeable and allows the P2P-CS transport solution to be managed without third parties. The effectiveness of the proposed approach has been verified by several tests carried out on real and simulated data. The obtained results are satisfactory and encourage the adoption of these further sustainable travel mode opportunities.

Should my automated car drive as I do? Investigating speed preferences of drivengers in various driving conditions.

Studies investigating the question of how automated cars (ACs) should drive converge to show that a personalized automated driving-style, i.e., mimicking the driving-style of the human behind the wheel, has a positive influence on various aspects of his experience (e.g., comfort). However, few studies have investigated the fact that these benefits might vary with respect to driver-related variables, such as trust in ACs, and contextual variables of the driving activity, such as weather conditions. Additionally, the context of intermediate levels of automation, such as SAE level 3, remains largely unexplored. The objective of this study was to investigate these points. In a scenario-based experimental protocol, participants were exposed to written scenarios in which a character is driven by a SAE level 3 AC in different combinations of conditions (i.e., types of roads, weather conditions and traffic congestion levels). For each condition, participants were asked to indicate how fast they would prefer their AC to drive and how fast they would manually drive in the same situation. Through analyses of variance and equivalence tests, results showed a tendency for participants to overall prefer a slightly lower AC speed than their own. However, a linear regression analysis showed that while participants with the lowest levels of trust preferred an AC speed lower than theirs, those with the highest levels preferred an AC speed nearly identical to theirs. Overall, the results of this study suggest that it would be more beneficial to implement a personalization approach for the design of automated driving-styles rather than a one for all approach.

Improved Congestion Control in Wireless Sensor Networks Using Clustering with Metaheuristic Approach

The wireless sensor network (WSN) assists an extensive range of sensor nodes and enables several real-time uses. Congestion on the WSN is based on high pocket traffic and low wireless communication capabilities under network topology. Highly loaded nodes will consume power quickly and increase the risk of the network going offline or breaking. Additionally, loss of packet and buffer overflows would result in an outcome of increased end-to-end delay, performance deterioration of heavily loaded nodes, and transport communication loss. In this paper, a novel congestion control system is proposed to diminish the congestion on network and to enhance the throughput of the network. Initially, cluster head (CH) selection is achieved by exhausting K-means clustering algorithm. After the selection of cluster head, an efficient approach for congestion management is designed to select adaptive path by using Adaptive packet rate reduction (APTR) algorithm. Finally, Ant colony optimization (ACO) is utilized for enhancement of wireless sensor network throughput. The objective function increases the wireless sensor network throughput by decreasing the congestion on network. The proposed system is simulated with (Network Simulator NS-2). The proposed K-means C-ACO-ICC-WSN attains higher throughput 99.56%, 95.62% and 93.33%, lower delay 4.16%, 2.12% and 3.11% and minimum congestion level 1.19%, 2.33% and 5.16% and the proposed method is likened with the existing systems as Fuzzy-enabled congestion control through cross layer protocol exploiting OABC on WSN (FC-OABC-CC-WSN), Optimized fuzzy clustering at wireless sensor networks with improved squirrel search algorithm (FLC-ISSA-CC-WSN) and novel energy-aware clustering process through lion pride optimizer (LPO) and fuzzy logic on wireless sensor networks (EAC-LPO-CC-WSN), respectively. Finally, the simulation consequences demonstrate that proposed system may be capable of minimizing that congestion level and improving the throughput of the network.

An Optimization Model for Structuring a Car-Sharing Fleet Considering Traffic Congestion Intensity

Ever-growing mobility and traffic congestion within urban areas make the need for a sustainable form of transport inevitable. Traffic congestion has a significant effect on the amount of energy consumption of a vehicle and, as a result, on its associated environmental impacts. Any decision-making regarding structuring a fleet without taking into account the traffic congestion level (TCL) will lead to a less sustainable fleet with higher environmental and economic costs. To address this issue, this study examines the effects of the traffic congestion intensity level on the fleet structure of an urban car-sharing company over a certain planning period. We present a new optimization framework for finding an optimal vehicle composition of the fleet of an urban car-sharing company considering the energy consumption of vehicles at different traffic congestion levels. The results show that electric vehicles (EVs) are more competitive than diesel vehicles (DVs) in high-peak traffic congestion from the outset of the planning period. In addition, we perform a sensitivity analysis to take into account the effects of specific uncertain parameters such as the energy and purchasing costs of EVs on the total cost of ownership. As expected, the purchasing price of EVs, energy prices of DVs, and increase in diesel prices have the highest impact on the total cost.

A pure number to assess “congestion” in pedestrian crowds

The development of technologies for reliable tracking of pedestrian trajectories in public spaces has recently enabled collecting large data sets and real-time information about the usage of urban space and indoor facilities by human crowds. Such an information, nevertheless, may be properly used only with the aid of theoretical and computational tools to assess the state of the crowd. As shown in this work, traditional assessment metrics such as density and flow may provide only a partial information, since it is also important to understand how “regular” these flows are, as spatially uniform flows are arguably less problematic than strongly fluctuating ones.Recently, the Congestion Level (CL), based on the computation of spatial variation of the rotor of the crowd velocity field, has been proposed as an assessment metric to evaluate the state of the crowd. Nevertheless, the CL definition was lacking sound theoretical foundations and, more importantly, was of very difficult interpretation (it was difficult to understand “what” CL was measuring). As we believe that such theoretical shortcomings were limiting also its relevance to applied studies, in this work we clarify some aspects concerning the CL definition, and we show that such an assessment metric may be improved by defining a dimensionless Congestion Number (CN).As a first application of the newly defined CN indicator we first focus on the cross-flow scenario and, by using discrete and continuous toy models, idealised “limit scenarios”, more realistic simulations and finally data from experiments with human participants, we show that CN≪1 corresponds to a crowd with a regular and safe motion (even in high density and high flow settings), while CN≈1 indicates the emergence of a congested and possibly dangerous condition. We finally use the CN indicator to analyse and discuss different settings such as bottlenecks, uni-, bi- and multi-directional flows, and real-world data concerning the movement of pedestrians in the world’s busiest railway station.

Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda

The implementation of autonomous delivery solutions in last-mile logistics operations is considered promising. Autonomous delivery solutions can help in tackling urban challenges related to last-mile logistics operations. Urbanization creates higher mobility and transportation demand, which contributes to increased congestion levels, traffic, air pollution, and accident rates. Moreover, mega-trends, such as e-commerce, demand that logistics companies react to increased customer expectations in terms of delivery time and service. Concerning service, electrified autonomous delivery solutions have the potential to operate 24/7 and can help to overcome driver shortages. This paper conducts a systematic literature review. Based on the literature set, a snowballing procedure was applied. Complementary gray literature was included. This work discusses different autonomous delivery solutions such as Autonomous Delivery Robots (ADRs), Unmanned Aerial Vehicles (UAVs), two- or multi-tiered systems, and the concept of passenger and freight integration. The work presents advantages and disadvantages, enabling the comparison of solutions. Furthermore, a research agenda is provided, from which practical-managerial and theoretical implications can be derived. The research agenda can help researchers, manufacturers, businesses, and governmental institutions to prepare for the arrival and subsequent implementation of autonomous delivery services. Various implications related to energy demand, legislation, implementation strategy, training, and risk and safety are presented. The outcome of this work calls for collaboration among various stakeholders, encourages mutual learning, and hints at the importance of national and international development projects.

Efficient Distributed MAC for Dynamic Demands: Congestion and Age Based Designs

Future generation wireless technologies are expected to serve an increasingly dense and dynamic population of users that generate short bundles of information to be transferred over the shared spectrum. This calls for new distributed and low-overhead Multiple-Access-Control (MAC) strategies to serve such dynamic demands with spectral efficiency characteristics. In this work, we address this need by identifying and developing two fundamentally different MAC paradigms: (i) congestion-based paradigm that estimates the congestion level in the system and adapts to it; and (ii) age-based paradigm that prioritizes demands based on their ages. Despite their apparent differences, we develop policies under each paradigm in a generic multi-channel access scenario that are provably throughput-optimal when they employ any asymptotically-efficient channel encoding/decoding mechanism. We also characterize the stability regions of the two designs, and investigate the conditions under which one design outperforms the other. We perform extensive simulations to validate the theoretical claims and investigate the non-asymptotic performances of our designs.

Fuel Consumption of Passenger Cars at Different Levels of Traffic Congestion and Traffic Conditions in Urban Cities of Sarawak

Fuel Consumption of Passenger Cars at Different Levels of Traffic Congestion and Traffic Conditions in Urban Cities of Sarawak

Control Technique for Plug-in Hybrid Power Buses to Distribute Energy

This research focuses on the development of a control method for plug-in hybrid power buses, specifically aimed at optimizing energy distribution in urban environments. The method utilizes GPS navigation and a digital map to obtain real-time vehicle position information and assess road congestion levels. By considering factors such as congestion, vehicle position, and battery electric quantity, the method enables dynamic optimization and adjustment of energy distribution. The objective of this research is to reduce fuel consumption, minimize pollutant emissions, and enhance fuel economy in plug-in hybrid power buses operating on fixed routes.

Virtual Local Area Network Performance Improvement Using Ad Hoc Routing Protocols in a Wireless Network

Wireless Communication has become one of the most popular types of communication networks because of the many services it provides; however, it has experienced several challenges in improving network performance. VLAN (Virtual Local Area Network) is a different approach which enables a network administrator to create a logical network from a physical network. By dividing a large network into smaller networks, VLAN technology improves network efficiency, management, and security. This study includes VLAN for wireless networks with mobile nodes integration. The network protection was improved by separating the connections and grouping them in a way that prevents any party from being able to contact unauthorized stations in another party using VLAN. VLAN demonstrated restricted access to private server data by managing traffic, improving security, and reducing levels of congestion. This paper investigates the virtual local area network in a wireless network with three ad hoc routing protocols in a number of different scenarios, using the Riverbed Modeler simulation, which was used as a simulation program in this study. It was found from the investigation process that adopting VLAN technology could reduce delay and data of the network and considerably lower throughput, which is a major drawback of VLAN. Ad hoc routing algorithms, including AODV (Ad Hoc On-Demand Distance Vector), DSR (Dynamic Source Routing), and OLSR (Optimized Link State Routing) routing protocols, were used to improve the delay and throughput of the network. Routing methods with VLAN were tested across the WLAN to obtain the best throughput gain performance. The findings also revealed that these ad hoc routing protocols improved the Wireless Sensor Network performance as an additional investigation for the improvement of any network’s delay and throughput.

ANALISA KINERJA LALU LINTAS RUAS JALAN SEMARANG – GROBOGAN PADA PERSIMPANGAN PASAR KARANGAWEN KABUPATEN DEMAK

ABSTRACT. This type of research is quantitative research. The problems in this study are 1) The factors that cause traffic jams on the Semarang-Grobogan Karangawen Demak road. 2) the performance of the unsignalized intersection on the Semarang-Grobogan Karangawen Demak road. This type of research is quantitative research. Based on the analysis, the results for side resistance are 1215.2 vehicles/hour for the east direction and 1162.7 vehicles/hour for the west direction, so the side resistance class for the east and west directions is very high (VH) because the total weight is greater than 900 vehicles/hour with conditions of commercial areas and high activity on the side of the road. The level of congestion with traffic volume in the west is 3122 pcu/hour and 1686 pcu/hour in the east and a capacity of 1469.52 pcu/hour for the west and east and the degree of saturation is 0.87 for the west and 0.54 for the east direction east.Keywords: factors causing congestion, performance of unsignalized intersections.

The Impact of Three Specific Collaborative Merging Strategies on Traffic Flow

On-ramps are considered to be one of the common traffic bottlenecks. In order to improve the operation efficiency of on-ramps, scholars worldwide have proposed various vehicle merging strategies. In this study, we designed different rules to express three collaborative strategies and studied their impact on on-ramp systems. Cellular automata models were used to simulate the systems under different situations, and the average speed and traffic flow rate of both the main roads and ramps were analyzed. The results show that (1) all the three merging strategies give excessive “priority” to the merging vehicle, leading to a severe reduction in the traffic performance of the main road; (2) nevertheless, these strategies have different effects on the entire system with a one-lane or two-lane main road. Due to the lane-changing behavior, the system with a two-lane main road has more advantages than that featured with a one-lane road, making the former system performing better than the latter under the same strategies; (3) the vehicles on the ramp and main road affect each other, and as the vehicle entering probabilities become large, the traffic flow rate on the main road decreases whereas that on the ramp increases. However, the effect is not unlimited, the flow rate on both roads finally reaches a stable level (forming a “platform”); and (4) large values of the merging safety distance parameter decrease the flow rate of the entire system. All the previous results provide a deep understanding of the impact of the three merging strategies on traffic flow, contributing to the design of on-ramp systems that have better operation efficiency and low levels of congestion.

Congestion Modelling and Level of Service Assessment of Urban Roads in Mixed Traffic Conditions

Congestion Modelling and Level of Service Assessment of Urban Roads in Mixed Traffic Conditions

Characteristics of pedestrians descending on a stairway: A trajectory-based empirical analysis

In this paper, we make a systematic analysis on movement characteristics of descending pedestrians on a stairway. According to the clustering of pedestrian lanes, the average distance between two adjacent lanes is 0.52 m under four-lane condition, while it is 0.64 m under three-lane condition. The innermost lane is found to be narrower than other lanes when the density is relatively high. With the decrease of density, the spatial distribution of the nearest neighbor becomes less condensed and its shape also gets more elliptical. On the stairs pedestrians sometimes allow the nearest neighbor to be in the front and back, while on level ground they tend to avoid the nearest one being located in these positions. Along the movement direction, pedestrian speed will first increase and then decrease, and then on the last tread before reaching the stair landing, there will be a sudden increase of speed. According to the individual fundamental diagram, the speed on the stairs is significantly lower than that on level ground, but the speed difference will become smaller with the increase of density. The values of congestion level and crowd danger are larger on the stairs than on level ground when the density is higher than 1.4 ped/m2. This demonstrates that movements on the stairs are more dangerous than those on level ground. It is hoped that the results obtained in this study can be helpful to pedestrian management on the stairs and the validation of stair evacuation models.

The Impact of Ride-Hailing Services on Congestion: Evidence from Indian Cities

Problem definition: Early research has documented significant growth in ride-hailing services worldwide and allied benefits. However, growing evidence of their negative externalities is leading to significant policy scrutiny. Despite demonstrated socioeconomic benefits and consumer surplus worth billions of dollars, cities are choosing to curb these services in a bid to mitigate first order urban mobility problems. Existing studies on the congestion effects of ride-hailing are limited, report mixed evidence, and exclusively focus on the United States, where the supply consists primarily of part-time drivers. Methodology/results: We study how the absence of ride-hailing services affects congestion levels in three major cities in India, a market where most ride-hailing drivers participate full time. Using rich real-time traffic and route trajectory data from Google Maps, we show that in, all three cities, periods of ride-hailing unavailability due to driver strikes see a discernible drop in travel time. The effects are largest for the most congested regions during the busiest hours, which see 10.1%–14.8% reduction in travel times. Additionally, we provide suggestive evidence for some of the mechanisms behind the observed effects, including deadheading elimination, substitution with public transit, and opening up of shorter alternative routes. Managerial implications: These results suggest that despite their paltry modal share, ride-hailing vehicles are substituting more sustainable means of transport and are contributing significantly to congestion in the cities studied. The reported effect sizes quantify the maximum travel time gains that can be expected on curbing them. Funding: This work was supported by the Srini Raju Center for Information Technology and the Networked Economy at Indian School of Business. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1158 .

An empirical investigation of driver car-following risk evolution using naturistic driving data and random parameters multinomial logit model with heterogeneity in means and variances

This study aims to address the questions of how driving risk evolves during car-following processes and what factors contribute to the underlying evolution patterns. An empirical study is conducted using real world car-following data collected in the Shanghai Naturalistic Driving Study (SH-NDS). The evolution of the driving risk induced by the dynamic coupling between the leading and following vehicles during the car-following process is characterized by how an instantaneous crash-risk measure - rear crash risk index (RCRI) - changes by time. A spectral clustering analysis is first conducted to classify the driving risk evolution of the observed car-following maneuvers, showing the existence of five distinctive risk evolution patterns in the car-following processes. In order to investigate the relationship between the identified driving risk evolution clusters and their contributing factors, a regression analysis employing a random parameter multinomial logit model with heterogeneity in means and variances is followed, revealing several significant contributing factors to the car-following risk evolution patterns, such as congestion level, driver’s ability to maintain stable headways, and vehicle deceleration. This study has provided important insights into driving risk from the new perspective of risk evolution patterns, which is expected to have significant implications for the future development of advanced traffic management and traveler information systems (ATMS/ATIS) strategies, advanced driver assistance systems (ADAS), and connected and autonomous vehicles (CAV).

Kajian Kehandalan Saluran Drainase dengan Pendekatan Metode First-Order Second Momentdan Safety Factor

The growth and development of big cities in Indonesia is quite fast. Especially the city of Bandung which is the center of tourism in the West Java region. Ir. H. Juanda street is one of the access to tourism places in Bandung City and is an icon of Bandung City. In addition, Ir.H Juandastreet has problems, namely high levels of congestion and flooding in the rainy season. The last ten years the Jalan Ir.H. Djuanda always floods when there is heavy rain. This causes puddles of water to enter the Jalan Ir. H. Juanda section, namely from Pasar Simpang to Dago Terminal. This has an impact on road damage, drainage, and congestion. To determine the risk of overflow of the channel in the study area as a result of various amounts of flood discharge, carried outthree analyzes stages, namely hydrological analysis to determine the amount of return period discharge, hydraulic analysis to identify overflow points and improvement scenarios and reliability analysis using the safety factor and first-order-second moment methods. The results of the analysis show that there are 2 points that have the opportunity for overflow, namely at the location of the Al-Ihsan Mosque and the Honda Workshop. The solution given to overcome this is to normalize the drainage with a size of 1.5 m x 1.5 m from upstream to downstream.The results showed that the reliability of the channel increased to 92.96% (Two Years Return Period Discharge), 88.54% (Five Years Return Period Discharge) and 85.81% (Ten Years Return Period Discharge) for the Al-Ihsan Mosque channel and 100% (Two Years Return Period Discharge), 99.98% (Five Years Return Period Discharge) and 99.92% (Ten Years Return Period Discharge) for the Honda Workshop channel. The method in the risk analysis above can relate the probability of failure or exceedance to the expected success of the function of a drainage cross-sectional structure in accommodating flood flows.