Average Queue Length Research Articles

Efficiency of Vehicle Actuated traffic control on isolated intersection

This paper is described different strategies for traffic control and simulation, namely - Vehicle Actuated (VA) compared to Fixed Time (FT) traffic control. We are comparing and evaluating the impact of FT and adaptive traffic signal control strategies for one of the biggest and busiest intersections in Tashkent, the capital of Uzbekistan. The parameters used for comparing these strategies are the average vehicle travel times and average vehicle queue lengths. TRL TRANSYT 15 software was used to determine the fixed signal timing plan based on intersection geometry, inter-green matrix, and traffic flow. PTV VISSIM software is used for VA algorithm development and simulation to get the maximum and average vehicle travel times as well as queue lengths. It is shown that the parameter optimization can reduce the queue lengths down to 65% and the travel time down to 51%.

Throughput properties and optimal locations for limited deployment of Max-pressure controls

Max-pressure (MP) control is one of the few traffic signal controllers proven to maximize network throughput or maximally stabilize the network. According to the theoretical results published so far, it can stabilize a network if all intersections are equipped with MP control for all stabilizable demands. However, budget constraints may not allow the installation of MP control on all intersections. Previous work did not consider a limited number of MP controlled intersections while proving the stability properties. Therefore, it is not clear whether a network can still be stabilized with a limited deployment of MP control. Using Lyapunov drift techniques this paper proves that even with a limited deployment, MP control can stabilize a network within feasible demand. Then we present an optimization formulation to find the optimal intersections to install MP control given a limited budget. We also present a greedy efficient algorithm to solve that optimization problem and prove that the algorithm solves the problem to optimality. Numerical results from simulations conducted on the downtown Austin network using an in-house custom simulator called AVDTA are then presented. The change in theoretical maximum servable demands for different amounts of deployments obtained from the optimization problem seemed to match with simulation results most of the times. We found that limited deployment of MP control almost always performed better than random deployment of MP control in terms of servable stable demand. Average total queue length and link density were observed to decrease as the number of MP controls increased which indicates better network performance. Average travel times per vehicle also decreased with installations of MP controls which shows how the travelers would benefit from more MP controls.

Impact of Platooning Connected and Automated Heavy Vehicles on Interstate Freeway Work Zone Operations

Work zones pose mobility issues to the traveling public and safety challenges to travelers and road maintenance workers. These safety and mobility issues may be exacerbated by the presence of heavy vehicles. Connected and automated vehicle (CAV) technologies have been identified as a potential solution for these issues. This paper investigates the operational impacts of connected and automated heavy vehicles (CAHV) on freeway work zone operations on interstate highways. A microsimulation model, calibrated to empirical work zone field data, was used to study the operational impacts of CAHV platoons under various work zone and traffic conditions. It was found that, as the CAHV market penetration rate increases, the average work zone delay and queue length decreases. In addition, as the demand and heavy vehicle percentage increases, so do the benefits of using CAHV technology. For example, it was found that, when all heavy vehicles are classified as CAHV, the average flow rate is approximately 67% higher, and the maximum queue size and average delay decrease by approximately 97%. The methodology used in this paper will help transportation agencies as they design work zones to accommodate heavy vehicles equipped with CAV technologies.

A Novel Deep Reinforcement Learning Approach to Traffic Signal Control with Connected Vehicles

The advent of connected vehicle (CV) technology offers new possibilities for a revolution in future transportation systems. With the availability of real-time traffic data from CVs, it is possible to more effectively optimize traffic signals to reduce congestion, increase fuel efficiency, and enhance road safety. The success of CV-based signal control depends on an accurate and computationally efficient model that accounts for the stochastic and nonlinear nature of the traffic flow. Without the necessity of prior knowledge of the traffic system’s model architecture, reinforcement learning (RL) is a promising tool to acquire the control policy through observing the transition of the traffic states. In this paper, we propose a novel data-driven traffic signal control method that leverages the latest in deep learning and reinforcement learning techniques. By incorporating a compressed representation of the traffic states, the proposed method overcomes the limitations of the existing methods in defining the action space to include more practical and flexible signal phases. The simulation results demonstrate the convergence and robust performance of the proposed method against several existing benchmark methods in terms of average vehicle speeds, queue length, wait time, and traffic density.

Analysis on D2D Heterogeneous Networks with State-Dependent Priority燭raffic

In this work, we consider the performance analysis of state dependent priority traffic and scheduling in device to device (D2D) heterogeneous networks. There are two priority transmission types of data in wireless communication, such as video or telephone, which always meet the requirements of high priority (HP) data transmission first. If there is a large amount of low priority (LP) data, there will be a large amount of LP data that cannot be sent. This situation will cause excessive delay of LP data and packet dropping probability. In order to solve this problem, the data transmission process of high priority queue and low priority queue is studied. Considering the priority jump strategy to the priority queuing model, the queuing process with two priority data is modeled as a two-dimensional Markov chain. A state dependent priority jump queuing strategy is proposed, which can improve the discarding performance of low priority data. The quasi birth and death process method (QBD) and fixed point iteration method are used to solve the causality, and the steady-state probability distribution is further obtained.Then, performance parameters such as average queue length, average throughput, average delay and packet dropping probability for both high and low priority data can be expressed. The simulation results verify the correctness of the theoretical derivation. Meanwhile, the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.

ASSESSMENT OF QUALITY OF SERVICE CHARACTERISTICS OF SIMILAR TRAFFIC IN GSM STANDARD MOBILE TELECOMMUNICATION NETWORKS

P/M/1, which models the service processes of self-similar GPRS packet traffic in GSM standard mobile telecommunication networks, including Pareto and limited Pareto distributions, and fBM/D/1/∝ type single-channel mass service system, which takes into account the self-similarity of this traffic, has been viewed. Development of telecommunication networks. has gone through many different stages of development to the current modern networks, which eventually resulted in a large number of different types of mobile telecommunication networks. One of such networks is GSM (Global system for mobile communication) standard mobile telecommunication networks. In these networks, the directions of rapid development of modern service services are observed recently, one of these directions is the GPRS (General packet radio service) superstructure service, which is considered the superstructure of the GSM mobile network and carries out the transmission of data in packets. Analytical models of these systems are developed based on them Analytical methods have been proposed for evaluating relevant quality of service characteristics such as the relative average waiting time of packets in these systems, average queue length, buffer volume, and packet dwell time in the system. As well as the nature of the dependence of the shape parameter of the Pareto distribution on the Herst parameter was determined based on the experiment.

Analysis and prediction of UAV-assisted mobile edge computing systems.

As the demand for the internet of things (IoT) continues to grow, there is an increasing need for low-latency networks. Mobile edge computing (MEC) provides a solution to reduce latency by offloading computational tasks to edge servers. However, this study primarily focuses on the integration of back propagation (BP) neural networks into the realm of MEC, aiming to address intricate network challenges. Our innovation lies in the fusion of BP neural networks with MEC, particularly for optimizing task scheduling and processing. Firstly, we introduce a drone-assisted MEC model that categorizes computation offloading into synchronous and asynchronous modes based on task scheduling. Secondly, we employ Markov chains and probability-generation functions to accurately compute parameters such as average queue length, cycle time, throughput, and average delay in the synchronous mode. We also derive the first and second-order derivatives of the probability-generation function to support these computations. Finally, we establish a BP neural network to solve for the average queue length and latency in the asynchronous mode. Our results from the BP neural network closely align with the theoretical values obtained through the probability-generation function, demonstrating the effectiveness of our approach. Additionally, our proposed UAV-assisted MEC model outperforms the synchronous mode. Overall, our MEC scheduling approach significantly reduces latency, enhances speed, and improves throughput, with our model reducing latency by approximately 11.72$ \% $ and queue length by around 9.45$ \% $.

Back-Pressure traffic Signal Control in the Presence of Noisy Queue Information*

In this paper, we consider centralized traffic signal control policies using the max-weight algorithm when the queue size measurement is noisy. We first show analytically that the standard max-weight algorithm is throughput optimal even under noisy queue measurements. However, the average steady-state queue lengths and subsequently the average delays are increased. In order to alleviate the effect of these noisy measurements we add filtering to the max-weight algorithm; more specifically, we propose the Filtered-max-weight algorithm, which is based on particle filtering. We demonstrate via simulations that the Filtered-max-weight algorithm performs better than the standard max-weight algorithm in the presence of noisy measurements.

Performance analysis of a two-level polling control system based on LSTM and attention mechanism for wireless sensor networks.

A continuous-time exhaustive-limited (K = 2) two-level polling control system is proposed to address the needs of increasing network scale, service volume and network performance prediction in the Internet of Things (IoT) and the Long Short-Term Memory (LSTM) network and an attention mechanism is used for its predictive analysis. First, the central site uses the exhaustive service policy and the common site uses the Limited K = 2 service policy to establish a continuous-time exhaustive-limited (K = 2) two-level polling control system. Second, the exact expressions for the average queue length, average delay and cycle period are derived using probability generating functions and Markov chains and the MATLAB simulation experiment. Finally, the LSTM neural network and an attention mechanism model is constructed for prediction. The experimental results show that the theoretical and simulated values basically match, verifying the rationality of the theoretical analysis. Not only does it differentiate priorities to ensure that the central site receives a quality service and to ensure fairness to the common site, but it also improves performance by 7.3 and 12.2%, respectively, compared with the one-level exhaustive service and the one-level limited K = 2 service; compared with the two-level gated- exhaustive service model, the central site length and delay of this model are smaller than the length and delay of the gated- exhaustive service, indicating a higher priority for this model. Compared with the exhaustive-limited K = 1 two-level model, it increases the number of information packets sent at once and has better latency performance, providing a stable and reliable guarantee for wireless network services with high latency requirements. Following on from this, a fast evaluation method is proposed: Neural network prediction, which can accurately predict system performance as the system size increases and simplify calculations.

Evaluation of Back of Queue at Signalized Intersections in Erbil City Using Different Software

Aims: The aim of this study is to evaluate the queue length of isolated signalized intersections, which used HCS2010 and SIDRA Intersection 8 traffic software. Background: One of the important parameters to evaluate the performance of a traffic management system is queue length, especially in congested traffic situations. For the estimation of back of queue length, many traffic analyzing models are used based on Highway Capacity Manual (HCM2010). Objective: The values of queue length obtained from these two softwares are to be compared with observed queue length from the field. The study also aids in conducting a model of optimization for the back of queue length to decrease the value of storage length of vehicles following the GA procedure. Methods: In this study, four isolated signalized intersections were used in Erbil city, the capital of the Iraqi Kurdistan Region. The values of the measured back of queue lengths are compared with the values obtained from Highway Capacity Software HCS2010(HCS+T7F) and Signalized and Unsignalized Intersection Design and Research (SIDRA Intersection 8) Aid Australian Road Research Board (ARRB) software. Results and Discussion: The results of regression analysis showed that the SIDRA Intersection 8 Back of Queue model with adjusted R2 0.8465 have a stronger relationship with the field measured Back of the Queue for linear relationship compared to the HCS2010 back of queue model. Furthermore, the study tends to optimize the signalized intersections under study using HCS2010 and SIDRA Intersection 8 software based on the Genetic Algorithm (GA) to minimize the back of queue length. The percent of average reduction in HCS2010 and SIDRA Intersection 8 back of queue models are 36% and 29%, respectively. The main objective of optimizing the timing plan was to minimize the average storage queue length at signalized intersections that follow the Highway Capacity Manual (TRB 2010) procedure for queue length calculation. Moreover, 95th and 98th values of the percentiles were chosen to estimate the expectancy of upstream lane blockage and the expectancy of short lane overflow that was related to the back of the queue percentile. Conclusion: The improvement of vehicle storage for upstream lanes was conducted by the two software systems mentioned before. The results showed significant improvement in the performance of the intersections under study with a reduction in queue length.

Simulation Based Analysis of Hierarchical Timed Colored Petri Nets Model of the Restaurant Food Serving Process

The major goal of establishing a restaurant is improved earnings making which can be jeopardized by customers' withdrawals due to lengthy ready lines. The above scenario was studied in this paper using simulation-based analysis of a Hierarchical Timed Coloured Petri Nets (HTCPN) model, which abstracted the serving operation of a renowned restaurant in the Ibadan metropolis. The restaurant was characterized by two or more servers that serially served each Customer from the multiple available servers at the four serving points. One hundred simulation runs were carried out on the HTCPN model using CPN Tools to determine the four (4) parameters,Customers' Average Flow Time (CAFT),Customers' Average Waiting Time (CAWT),Servers' Average Utilization Rate (SAUR) andCustomers' Average Queue Length (CAQL) required in serving 567, 1100, 1103, 770 and 829 customers from Monday to Friday, respectively. The model was validated by carrying out a statistical analysis t-Test between the simulated and the actual customers' flow time andservers' utilization rate at a 5% significant level. The validation results showed no significant differences between the simulated and the actual customers' average flow time andservers' utilization rate at a 5% significance level. Hence, the model can represent the restaurant under consideration.

Classical and Bayesian estimations of performance measures in a single server Markovian queueing system based on arrivals during service times

The present study considers a single-server Markovian queueing system by observing the number of customer arrivals during the service time of a customer. We estimate the traffic intensity in this queueing system along with the average queue length and the expected number of customers in the system. We propose classical and Bayesian frameworks to estimate the parameters of interest. In the Bayesian setup, three forms of prior distributions for ρ and two loss functions are considered. Furthermore, the predictive distribution of the number of customer arrivals during the service time of a customer and the equal-tailed credible region of ρ are obtained. The aforementioned approaches are illustrated with numerical examples based on simulation studies.

Dynamic user optimal route choice problem on a signalized transportation network

In this paper, we present a new route-based discrete time variational inequality (VI) ideal dynamic user optimal route choice (DUO) model on a transportation network with fixed signal timing at signalized intersections and a relaxation with gradient projection algorithm to solve the model. The new trait of our study is the queue length in red time and the throughput in green time for each cycle at each intersection can be found when traffic is in DUO status. This is different from other studies, in which either only average queue length or average delay in a period composing of multiple cycles can be found or traffic is not in DUO status. Furthermore, the optimal signal timings can be found by the algorithm. Under optimal signal timing, the total queuing delay of the network reaches minimum when traffic is in DUO status.

Efficiency Assessment of New Signal Timing in Saudi Arabia Implementing Flashing Green Interval Complimented with Law Enforcement Cameras

Traffic congestion at intersection is one of the significant socioeconomic concerns worldwide. To tackle this challenge, researchers and practitioners are researching and executing different plans to control and manage long queues and delays. The general department of traffic in Saudi Arabia has implemented a new signal timing pattern in a number of signalized intersections that were designed with an additional flashing green phase complemented with law enforcement cameras (SAHER) to improve the capacity and safety of signalized intersections. This research aims to evaluate the impact of flashing green intervals on driver behavior and traffic efficiency of five signalized urban intersections equipped with SAHER in the Al-Qassim region, Saudi Arabia. Analyses for the current situation (base scenario) and proposed scenarios (without SAHER) are performed and validated using the microsimulation model (VISSIM) with field collected data at the selected intersections. The results showed that, despite fewer improvements in vehicle delays, the intersections without SAHER and flashing green intervals yield shorter queue lengths than the intersections with SAHER and flashing green intervals. Further, it was also revealed that drivers tend to stop early and start late in the case of SAHER due to fear of red light fines, thus not utilizing the full green split and yellow time. Analysis for the average vehicle delay and queue lengths is also conducted to assess the efficacy of implemented green light flashing with SAHER on driver behavior and operational efficiency of the selected intersections.

Land side truck traffic modeling at container terminals by a stationary two-class queuing strategy with switching

PurposeThis paper evaluates an alternative queuing concept for marine container terminals that utilize a truck appointment system (TAS). Instead of having all lanes providing service to trucks with appointments, this study considers the case where walk-in lanes are provided to serve those trucks with no appointments or trucks with appointments but arrived late due to traffic congestion.Design/methodology/approachTo enable the analysis of the proposed alternative queuing strategy, the queuing system is shown mathematically to be stationary. Due to the complexity of the model, a discrete event simulation (DES) model is used to obtain the average waiting number of trucks per lane for both types of service lanes: TAS-lanes and walk-in lanes.FindingsThe numerical experiment results indicated that the considered queuing strategy is most beneficial when the utilization of the TAS lanes is expected to be much higher than that of the walk-in lanes.Originality/valueThe novelty of this study is that it examines the scenario where trucks with appointments switch to the walk-in lanes upon arrival if the TAS-lane server is occupied and the walk-in lane server is not occupied. This queuing strategy/policy could reduce the average waiting time of trucks at marine container terminals. Approximation equations are provided to assist practitioners calculate the average truck queue length and the average truck queuing time for this type of queuing system.

METHODOLOGICAL APPROACH TO DETERMINATION OF EVACUATION BASIC PARAMETERS OF INJURED PERSONNEL OF OPERATIONAL GROUPING OF TROOPS USING DIFFERENT MEANS OF TRANSPORT

The timing of the evacuation of the wounded is a critical factor that largely determines the fate of the injured soldier. At present, despite considerable efforts to provide the Armed Forces of Ukraine with weapons and military equipment as well as logistical support, including medical equipment and assets, in particular basing as well on international technical aid, the problem of the absence of the required number of specialized medical evacuation means has not been resolved.
 From this point of view, the question of the correct formation of requirements for rational composition and specially equipped various types of vehicles (including sanitary transporters, ambulances), also general use, casualty evacuation systems, Identifying the possibility of its further improvement through the methodological apparatus is topical.
 The existing system of military evacuation of the injured and ill people is a four level system where all critically and moderately injured are evacuated. Regarding this, the evacuation system of the injured persons might be considered as queuing network, which has a range of peculiarities. First of all this network of queuing is an open network of queuing service, in other words the flow of applications for the network input is unlimited, homogeneous and is carried out from an external independent source. As a result of the calculations the data were received on the figures of network parameters (average number of requests in queues, average number of requests in the network, average waiting time for requests in service queues, average time of request in the network) and parameters of each queuing system which is operating in the network queuing, – transmission ratio, input flow intensity, downloading ratio, average number of occupied channels, average number of requests in the queuing system, average queue length, average waiting time of the request in the queue for being served, the average time of the request in the queuing system. Analyzing the calculated data from the point of view of creating a rational open queuing network, the system of the injured persons evacuation reaches its maximum efficiency when its productivity on processing the incoming flow of the requests is on its maximum level, and such parameters as the number of service requests in the queue and the number of service channels operating in the network are on its minimum level.

New Possibilities of Queuing Systems with Time Delay

From the classical theory of queuing, it is known that the average delay of requests in the queue is directly proportional to the variances of random intervals between arrivals of requests and service time, which means that it depends quadratic on the coefficients of variation of these random variables. Classical QS are applicable only in the case of fixed values of these coefficients of variations, which is a serious limitation for them. In contrast to the classical theory, the article presents the results of research on QS described by distribution laws shifted to the right from the zero point. Such a transformation of distribution laws with the introduction of a time shift parameter increases the mathematical expectations of random arrival and service intervals. This, in turn, reduces the coefficients of variation of time intervals, and, consequently, the average delay of requests in the queue will decrease many times depending on the value of the shift parameter. In the previous works of the author, spectral solutions and calculation formulas obtained on their basis for the average delay of requests in the queue for a set of QS with time delay are presented. These systems are obtained using four distribution laws used in queuing theory: exponential, hyperexponential, Erlang and hyper-Erlang. It has been theoretically and practically proven that in systems with a time delay, the average delay is less than in classical systems with the same load. Taking into account the Little formulas that fix the dependence of such QS characteristics as the average queue length, the average number of requests in the system, and the average residence time of requests on the average delay, we obtain an important feature for systems with delay. The distribution law shift parameter can regulate the average delay, and through it the other characteristics of the QS.

Application of queuing theory and simulation to reduce waiting time in dental hospitals

Background: Patient waiting time is an important factor in the management of the health sector. This study aimed to develop a suitable queuing theory and simulation technique to optimize dental hospital management.Methods: A descriptive-analytical study was performed in a dental hospital in Tehran, Iran. A sample of 3364 patients referred to the hospital was selected to calculate the patient flow and queuing system performance. After an initial data assessment, the dental hospital queuing system performance indicators were calculated for two shifts. The queuing system of the current situationwas modeled using ARENA software, and two scenarios were examined.Results: The average number of patients waiting in the queuing system was 38 and 17 in the morning and evening, respectively. The average time patients spend waiting in the system was 110 and 49 minutes in the morning and evening, respectively. The two scenarios, based on the simulated queuing network model, showed that in the first scenario, by using two nurses (one male and one female) as triage clerks for filing requests, one clerk for managing financial records, and one information desk secretary, the average queue length and waiting time were reduced to 0.02 patients and 4 minutes, respectively. In the second scenario, by using two nurses (one male and one female) as triage clerks for filing requests and two secretaries (one male and one female) for financial record management and registration, the average queue length and the waiting time in triage were reduced to 0.03 people and 5 minutes, respectively.Conclusion: Based on the results, using queuing theory and simulation techniques can improve the queuing status of health centers without any changes in the number of staff and only by implementing a suitable rearrangement in staff duties, establishing parallel service lines in busy service-providing centers, and using nurses able to multitask.

Online Resource Management of Heterogeneous Cellular Networks Powered by Grid-Connected Smart Micro Grids

This paper investigates a long-term average total energy cost minimization problem via resource management, including admission control, power allocation, and Energy Sharing (ES) of renewable energy in Heterogeneous Cellular Networks powered by Grid-connected Smart Micro Grids (GSMG-HCNs). In GSMG-HCNs, both renewable and grid energy power the base stations. Unlike existing works, we consider the cost of both renewable and grid energy and formulate the power line loss process caused by ES into our model. To solve the proposed problem, we transform it into a real-time issue by the Lyapunov technique. The proposed Cost-Aware Online Resource Management (CAORM) algorithm decouples the real-time issue into two sub-problems, one of which is linear and the other is addressed based on the successive convex approximation approach. We theoretically prove the asymptotic optimality of the CAORM algorithm and a tradeoff between the average total energy cost and the average queue length. Simulation results reveal that the CAORM algorithm outperforms benchmarks in reducing total energy cost and can make appropriate decisions according to different unit costs of renewable energy. Besides, the designed distance-related ES loss rate can help obtain better solutions with lower ES losses.

Stability and average delay in delay tolerant networks with Poisson packet arrivals and buffered relay nodes

We consider a single-source single-destination delay tolerant network (DTN) with Poisson packet arrivals. The source uses a store and forward protocol which makes multiple copies of a packet to relays which buffer them until delivery to the destination. We characterize the stability threshold, defined as the maximum value of arrival rate for which the source has finite average queue length, as a function of number of relays, relay contact rate, relay packet buffer capacity, and number of packet copies. We analyse DTNs without packet delivery feedback and with instantaneous feedback. For DTNs without packet delivery feedback, we obtain a non-asymptotic analytical stability threshold and show that it only doubles as the relay-buffer capacity increases from one to infinity. For DTNs with instantaneous packet delivery feedback, we characterize the stability threshold using simulations. We also present an analytical approximation for the stability threshold in the case of unit relay-buffer capacity, and show that it is approximately double of that without feedback for large number of packet copies and relays. For DTNs with and without feedback, we also study the average delay performance through simulations. We obtain analytical approximations for the average delays of the packets for DTNs without feedback. We observe that the last-in-first-out relay to destination packet transmission policy has the minimum delay.