Nowadays, the number of vehicles has increased exponentially, but the bedrock capacities of roads and transportation systems have not developed in an equivalent way to efficiently cope with the ...number of vehicles traveling on them. Due to this, road jamming and traffic correlated pollution have increased with the associated adverse societal and financial effect on different markets worldwide. A static control system may block emergency vehicles due to traffic jams. Wireless Sensor networks (WSNs) have gained increasing attention in traffic detection and avoiding road congestion. WSNs are very trendy due to their faster transfer of information, easy installation, less maintenance, compactness and for being less expensive compared to other network options. There has been significant research on Traffic Management Systems using WSNs to avoid congestion, ensure priority for emergency vehicles and cut the Average Waiting Time (AWT) of vehicles at intersections. In recent decades, researchers have started to monitor real-time traffic using WSNs, RFIDs, ZigBee, VANETs, Bluetooth devices, cameras and infrared signals. This paper presents a survey of current urban traffic management schemes for priority-based signalling, and reducing congestion and the AWT of vehicles. The main objective of this survey is to provide a taxonomy of different traffic management schemes used for avoiding congestion. Existing urban traffic management schemes for the avoidance of congestion and providing priority to emergency vehicles are considered and set the foundation for further research.
•We formulate a nonlinear programming model to devise demand-adapted timetables in a double-track urban rail transit line.•The dynamic behavior of passenger demand is incorporated into the model via ...cumulative demand curves.•The model takes into account left-behind passengers resulting from heavy congestion in trains.•Train departure times, running times between stations, and dwell times are optimized simultaneously.•The experimental results reveal that our approach is effective in reducing the average waiting time at stations.
Train timetable is of critical importance for an urban rail transit line, chiefly because it is the primary factor determining passenger perception of service quality. As it not only delivers efficient transit service to users but also significantly contributes to operator profitability, the train timetabling problem has been a widely studied subject in academic circles. Still, the existing models in the literature, for the most part, fail to sufficiently take into account train capacity, fleet size, and vehicle circulation. As a contribution to bridging this research gap, this study mainly focuses on the train timetabling problem in a congested urban rail corridor to adapt to dynamic behavior of passenger demand subject to operational and resource constraints. A nonlinear programming model is formulated to devise timetables with a view to minimizing the average waiting time per passenger. In the model, the congestion is represented by some passengers who may not be able to take the first incoming train due to limited train capacity. To evaluate the effectiveness of the proposed approach, a case study is performed on a metro line in Istanbul. According to study results, the optimized demand-oriented train timetable proved to be more advantageous when compared to its periodical counterpart prepared by traffic planners. Finally, a sensitivity analysis is conducted to attain the best trade-off between passenger satisfaction and operation cost.
•A path–indexed non–linear formulation of the train timetabling problem is presented.•The average passenger waiting time is affected by the headways.•Lagrangian relaxation algorithm could find ...optimal solutions in reasonable time.•The result shows that the hardness of the vehicle circulation constraint is dominant.
Delivering efficient transit services to users is the main objective of public transportation systems. Thus, rail transit systems seek to schedule train services in order to avoid passenger congestion and to minimize the waiting times for passengers. In this study, we present a path-indexed nonlinear formulation of the train timetabling problem for an urban railway system with the objective of minimizing the average waiting time per passenger subject to capacity and resource constraints. The number of planned train services is limited, so the main decisions involved in this scheduling problem are the optimal departure times for all the trains running on the network. A Lagrangian relaxation approach is proposed where the vehicle circulation constraints are relaxed, so the problem can be decomposed into a number of sub-problems for each path. We tested the proposed approach using realistic examples suggested by the Tehran sub-urban railway administration in Iran. The results obtained proved that the strength of the vehicle circulation constraint was dominant. The Lagrangian relaxation algorithm could find optimal solutions for large-scale problems within a reasonable run-time compared with traditional methods using commercial solvers, thereby suggesting the high potential of the proposed solution approach for a metro system.
•Two distribution-free runs rules Lepage and synthetic Lepage schemes are proposed.•The proposed schemes can jointly monitor the process location and scale parameters of any continuous process.•We ...investigate the performances of the proposed schemes compared to the existing Shewhart-Lepage scheme.•We recommend the 2-of-3 runs rules Lepage scheme due to its efficiency and simplicity.•We illustrate the applications of these schemes in monitoring the average daily customer waiting time of a service centre.
The average daily customer waiting time in a service centre is one of the most important metrics to measure performance or service quality. The average daily waiting time should meet a prespecified quality standard. Therefore, it is crucial to monitor such waiting times at regular intervals to maintain and improve the service quality. Similar problems arise in many time-between-event monitoring problems. This paper suggests two improved nonparametric Lepage schemes supplemented with runs rules, i.e., the 2-of-3 runs rules Lepage and the synthetic Lepage schemes. We show the real-life usage of the suggested schemes in monitoring the average daily customer waiting time of a service centre in Australia. The distribution-free nature of the suggested schemes allows broader applicability irrespective of the underlying process density. Moreover, the proposed schemes can jointly monitor the process location and scale parameters. We demonstrate the superiority of the suggested runs rules schemes to those without runs rules, i.e., the Shewhart-Lepage (SL) scheme through computer-intensive Monte-Carlo simulation. In general, we recommend the 2-of-3 runs rules Lepage scheme due to its efficiency and simplicity.
•We are the first to study charging issue for 3D underwater rechargeable sensor networks.•We develop a series of charging algorithms for enhancing energy efficiency.•Our schemes can save energy, save ...time, and ensure effective utilization of resources.
Recent breakthrough in wireless power transfer provides a new paradigm for enabling wireless energy replenishment for wireless rechargeable sensor networks, especially in the underwater environment. In this paper, we first propose the concept of UWRSNs (underwater wireless rechargeable sensor networks) and then develop a series of 3D charging schemes for enhancing charging efficiency, using underwater charging robot mules in three-dimensional charging scenarios. Through constructing the architecture of UWRSNs, we develop a basic charging scheme SCS (Shortest-path Charging Scheme), which minimizes the traveling cost for the charging mules in the 3D underwater environment. Then, ECS (Emergency Charging Scheme) is proposed, which concentrates on serving emergency nodes. After that, a charging algorithm that combines ECS and SCS to collaboratively solve the charging problem, namely, HOCS (Hybrid Optimal Charging Scheme) is developed. At last, experimental simulations are conducted to show the outperformed merits of the proposed scheme. Experimental results demonstrate that our schemes not only save energy and time, but also ensure effective utilization of resources.
The dependence of request servicing delay on the number of deployed containers is investigated for computer systems with container virtualization. The sought-after dependency is due to the allocation ...of limited computational resources of the computer system between active and inactive containers loaded in the system. The conducted research proposes a comprehensive combination of analytical queuing model, simulation modeling, and natural experiments. The studied computer system is interpreted as a multi-channel queuing system with an unlimited queue. The peculiarity of the proposed approach is the study of the influence of the number of containers formed in the system on queue delays and request servicing rate. Each container is associated with a service channel, and for the operation of a container in active and inactive states, the use of part of the common resources of the computing system is required. When constructing the model, it is assumed that the input flow is simple, and the service is exponential. The service rate depends on the number of deployed containers and the number of requests in the system. The experimental dependence of service rate on the number of active containers has been established. The experimental study was carried out on a platform based on Proxmox virtualization technology with fixed resources. To study the influence of the number of active containers on service rate within the experiment, a single-threaded web server was deployed in the form of several containers managed using the portable extensible Kubernetes k3s platform. The results of calculations using the analytical model are confirmed by the results of simulation modeling implemented using the SimPy modeling library in the Python programming language. Based on the conducted research, the need to solve the optimization problem of the number of deployable containers in a computer system regarding the influence of this number on request servicing delays is shown. The conducted research can find application in the design of real-time cluster systems critical to acceptable wait service delays, ensuring the continuity of the computational process, and preserving unique data accumulated during the system operation. The proposed approaches can be applied in the creation of fault-tolerant distributed computer systems, including those operating with failure accumulation and system reconfiguration with load (request) redistribution during dynamic container migration and replication.
In metro systems, the train passenger load is an important parameter that reflects both the utilization level of the trains provided by the operator and the comfort level of passengers in terms of ...crowdedness. In addition to minimizing the energy consumption and passengers' time cost, the train passenger load should also be optimized in order to maintain a high utilization rate of trains and an adequate level of comfort for passengers. In this paper, a multi-objective train timetable optimization procedure is proposed to minimize the total energy consumption, the average waiting time, and the average maximum load deviation. Case studies on the Beijing Yizhuang line show that the proposed approach could effectively reduce the total energy consumption, the average waiting time, and the average maximum load deviation, thus ensuring a high service quality and a low operational cost for the metro system.
In the new industrial revolution known as Industry 4.0, radio frequency identification (RFID) systems are a key component of automatic detection. These systems have two main elements, namely Reader ...and Tag. In many Internet of Things (IoT) applications, the RFID system is used with lots of readers working together in a dense environment to read tags. The simultaneous operation of readers with a common sensory range increases the likelihood of reader‐to‐tag collision and reader‐to‐reader collision and reduces the number of successful reading and as a result, reduces network performance and average waiting time for each reader increased. Collisions happen when readers are in the interference range and start reading tags simultaneously, so it is necessary to use the right solution to control channel access in these systems. So far, various solutions have been proposed to control readers’ access to the communication channel. Some of them have not considered the existing standards for this type of system or have not been efficient enough to be used in the IoT. In this study, we propose a method that, by considering the distance between readers and the number of neighbourhoods, and the possibility of information sharing, allows readers to successfully read more tags with fewer collisions in a certain time frame. The results of the performance study in a real‐world environment showed that the suggested method outperformed similar methods in terms of network performance and has much better throughput, making it a superior choice for usage in IoT‐based RFID systems.
In this study, we propose a method that, by considering the distance between readers and the number of neighbourhoods, and the possibility of information sharing, allows readers to successfully read more tags with fewer collisions in a specific time frame.
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