Heavy Traffic Situations Research Articles

Perceived Challenges and Effects of Flexible Learning at Ilocos Sur Polytechnic State College Tagudin Campus

Flexible learning modalities are implemented by learning institutions to address the challenges of pandemic, war, flood, heavy traffic, unbearable temperature and other extreme situations and to continue educating the learners. The study assessed the implementation of flexible learning modality among ISPSC Tagudin Campus students by identifying the challenges towards financial and psychological aspects including academic performances. The researchers used the descriptive research design and an online survey questionnaire was administered as the primary data gathering tool to 249 College of Arts and Sciences students as respondents. The collected data were subjected to simple statistical analysis such as frequency count, percentage, mean and Pearson Product Moment Coefficient Correlation (Pearson r). The researchers found out that the respondents were mostly young adults who belong to poor households and were residing in rural areas; they faced minor challenges in their online and modular distance learning and their financial, psychological, and academic performances were affected in the utilization of flexible learning modalities. Social class has a significant correlation on the challenges of using flexible learning modalities. Students are encouraged to consistently develop and maintain academic motivation while using the flexible learning modality (modular instruction, face-to-face learning delivery and online instruction). Despite adverse conditions being experienced, the college administration should provide ways and means to alleviate the financial difficulties of students through the provision of stable internet connection in school and the provision of online or printed learning materials to facilitate a healthy and conducive learning environment while on their online classes.

Evaluation of Drivers' Driving Behavior in Heavy Traffic Situations from OBD-II Data

The analysis and discussion of the onboard diagnostic data will help understand the driver's behavioral characteristics and develop a sustainable transportation system. The research content of this paper is to mine the driving behavior data through the vehicle preload equipment, analyze the factors affecting safe driving and establish a prediction model. This study collected data from 50 Taiwanese drivers while operating in heavy traffic. Understand the driver's behavioral characteristics through data analysis, such as calculating the times of the driver's emergency braking is based on the driving speed. From this result, the index of dangerous driving is defined. In addition, the dangerous driving index and other variables were analyzed, and it was found that there was a significant relationship between dangerous driving and vehicle mileage and maximum speed. According to the results, the drive speed increases the driving risk, the mileage reduces the risk probability, and the prediction accuracy is 78.9%. Complete data needs to be collected to evaluate complete driving behavior characteristics for developing sustainable transportation goals.

Comparative Analysis of Shortest Route Problem Algorithms for Emergency Response Services

Emergency response services require a fast and shortest possible route when responding to emergency situations that include road accidents, crimes, the occurrence of fires, etc. In this regard, an efficient and robust shortest route locator is essentially important. This study primarily aims to analyze the performance of the various shortest route problem algorithms, including the regular Dijkstra’s algorithm, the Bidirectional search algorithm, and the Multidirectional Dijkstra’s algorithm (MDA). The implementations of these algorithms are evaluated and compared in order to determine which algorithm can be an excellent choice to be adopted by such emergency response services. The results showed that the MDA has efficient performance in both light and heavy traffic situations in terms of speed and response times.

Predicting confirmation times of Bitcoin transactions

We study the distribution of confirmation times of Bitcoin transactions, conditional on the size of the current memory pool. We argue that the time until a Bitcoin transaction is confirmed resembles the time to ruin in a corresponding Cramer-Lundberg process. This well-studied model gives mathematical insights in the mempool behaviour over time. Specifically, for situations where one chooses a fee, such that the total size of incoming transactions with higher fee is close to the total size of transactions leaving the mempool (heavy traffic), a diffusion approximation leads to an inverse Gaussian distribution for the confirmation times. The results of this paper are particularly interesting for users that want to make a Bitcoin transaction during heavy-traffic situations, as evaluation of the well-known inverse Gaussian distribution is computationally straightforward.

Design and Implementation of an Emergency Traffic Light Pre-emption System Using PLC Automation

As traffic on the urban Ghanaian road network increases, congestion and delays are becoming more severe. Traffic signals are the most common method by which right of way is dynamically allocated to conflicting movements. Ghanaian traffic light control system is mainly designed by using devices such as timers, relays etc. The critical timing operation is required to be carried out under the existence of heavy traffic situations. This does not give this conventional traffic light control system the flexibility to control throughput to favor emergency vehicles. This conventional practice leads to many problems and subsequent delay for a long time. With the help of a PLC, the requirement of fast automation and effective optimization of traffic light control even in times of emergency can be achieved.At intersections, capacity bottlenecks are formed in urban road networks because at these locations, capacity must be shared by competing traffic movements. For this reason, this thesis introduces an execution and implementation of T-junction emergency traffic control system using SEIMENS S7-200 PLC. Programming in PLC is written in ladder logic with the help of STEP7 MICROWIN software.

교통혼잡 상황에서 운전자의 차선변경 행위와 의사결정

교통혼잡 상황에서 운전자의 차선변경 행위와 의사결정

Incremental Model Predictive Control of Active Suspensions With Estimated Road Preview Information From a Lead Vehicle

Abstract In preview-based vehicle suspension applications, the preview of the road profile is highly dependent on the preview sensors. In some scenarios such as heavy traffic situations, the preview of road profile can only be estimated by other vehicles because the view of the preview sensors may be blocked by other vehicles. The estimated preview road information can contain errors, which thus requires the controller to have a good robust performance. In this paper, an incremental model predictive control (MPC) strategy for active suspension systems along with a road profile estimator using preview information from a lead vehicle is proposed. The efficacy of the proposed strategy is experimentally validated on two scaled-down active suspension stations with comparison to two conventional active suspension control approaches.

Intersection management for autonomous vehicles with vehicle-to-infrastructure communication.

This paper proposes an intersection management strategy for autonomous vehicles under the vehicle-to-infrastructure circumstance. All vehicles are supposed to be fully autonomous and can communicate with the intersection management unit to check the traffic situation. Priority of passing the intersection is decided by a static conflict matrix which represents the potential conflict between lanes of different directions and a dynamic information list which could capture the real-time occupation of each lane in the intersection. Compared with the existing approaches in the literature, the intersection management unit in our strategy is more like a database rather than a computational center, and therefore, requires less computational resource and more likely satisfies the real-time requirement in heavy traffic situations. Simulations are conducted using SUMO (Simulation of Urban MObility), in which the proposed strategy is compared with both fixed and adaptive traffic light methods. The results indicate that the proposed strategy could significantly reduce the average time delay caused by the intersection and the corresponding variance, which shows the efficiency and fairness of the proposed strategy in intersection management.

Novel Multilayered Cellular Automata for Flying Cells Positioning on 5G Cellular Self-Organising Networks

There will be a profound impact from 5G to develop smart cities. Questions such as “How telecommunication operators will efficiently provide network infrastructure”, “When and where the quality of service parameters are degraded or below expected” are to be considered. In this context, the use of base stations carried by Unmanned Aerial Vehicles (UAV) acting as flying cells to compensate areas where telecommunications systems are challenged by abnormal conditions during their operation has attracted attention. In this paper, we propose an intelligent solution based on a novel multilayered cellular automata for positioning flying cells and improvement of network capacity in context heavy traffic situations as congested cars in avenues in some hours of the day, crowded events, disaster or hot spot traffic. In our distributed approach, all UAV base stations operate in parallel. The self-organisation arises from an emergent pattern based on applying simple rules in a defined neighbourhood. The proposed scheme considers both backhaul and radio access network constraints, and user requirements in terms of downlink throughput. Simulation results show that the proposed algorithm performs favourably compared with other schemes in terms of all metrics considered. Therefore, we provide a solution for rapid and efficient positioning of multiple UAV base stations to respond in real time to urgent network changes.

RETRACTED: Green corridor: A self-learning and educating algorithm for engineers (industry/students) to send data in emergency situations through wireless sensor network

Presently Wireless Sensor Network used to deploy at various critical locations where heavy traffic load situations along with priority-based data routing are always occurred. Under these situations...

Group-Signature and Group Session Key Combined Safety Message Authentication Protocol for VANETs

Anonymous authentication has significant contribution to privacy protection in safety message dissemination for Vehicular Ad Hoc Networks (VANETs); however, it suffers from heavy workload of vehicle revocation check and message signature verification, which leads to unsatisfactory timeliness and high message loss rate in heavy traffic situations. To manage these challenging problems, this paper proposes an efficient safety message authentication protocol for VANETs by combining batch group signature verification and our proposed Group Session Key (GSK). Specifically, our signature verification method for safety message can both achieve computation efficiency by reducing the number of computation operations of bilinear pairing and resist impersonation attack by using tracking key implement. GSK is associated with the forward and backward keys and is only shared among unrevoked vehicle within a group. Performance analysis and simulations demonstrate that our protocol can provide promising security against various common types of attackers and is more efficient than traditional group-signature-based authentication protocols, in terms of computation time cost, authentication delay and message loss rate.

Challenges for Older Drivers in Urban, Suburban, and Rural Settings.

Along with age-related factors, geographical settings—urban, suburban, and rural areas—also contribute to the differences in fatal crashes among older drivers. These differences in crash outcomes might be attributed to the various driving challenges faced by older drivers residing in different locations. To understand these challenges from the perspective of the older driver, a focus group study was conducted with drivers 65 and older from urban, suburban, and rural settings. Guided-group interviews were used to assess driving challenges, mobility options, opportunities for driver support systems (DSS), and alternate transportation needs. Content analysis of the interview responses resulted in four categories representing common challenges faced by older drivers across the settings: behavior of other drivers on the road, placement of road signs, reduced visibility of road signs due to age-related decline, and difficulties using in-vehicle technologies. Six categories involved location-specific challenges such as heavy traffic situations for urban and suburban drivers, and multi-destination trips for rural drivers. Countermeasures implemented by older drivers to address these challenges primarily involved route selection and avoidance. Technological advances of DSS systems provide a unique opportunity to support the information needs for route selection and avoidance preferences of drivers. Using the content analysis results, a framework was built to determine additional and modified DSS features to meet the specific challenges of older drivers in urban, suburban, and rural settings. These findings suggest that there is heterogeneity in the driving challenges and preferences of older drivers based on their location. Consequently, DSS technologies and vehicle automation need to be tailored to not only meet the driving safety and mobility needs of older drivers as a population, but also to their driving environment.

Congestion control with adaptive access class barring for LTE M2M overload using Kalman filters

In machine to machine (M2M) communication systems based on the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE), the machine type communication (MTC) devices compete in a random access channel (RACH) to access the network. An MTC device randomly chooses a preamble from a pool of preambles and transmits it during the RACH. The evolved node B (eNodeB) acknowledges the successful reception of a preamble if that preamble is transmitted by only one device. To reduce the burstiness of the connection requests in heavy traffic situations, access class barring (ACB) is proposed in the 3GPP standard. Using ACB, an MTC device postpones its request in a RACH with a probability p. In this paper, we propose a new adaptive ACB scheme for congestion control of bursty M2M traffic. The optimal value of the ACB depends on the total number of MTC devices competing in a RACH. To estimate this number, we derive a joint conditional probability distribution function (PDF) for the number of preambles selected by zero or one MTC device, conditioned on the number of MTC devices that passed the ACB check. We design a maximum likelihood estimator using this PDF. We use this estimation to dynamically adjust the ACB factor. To further improve our estimation, we use Kalman filtering based on the dynamics of the system for both known and unknown arrival distribution. In addition, for each device, we derive an approximate expression for the PDF of the delay to access the random channel. At the end, an energy consumption scheme for each MTC device is proposed while the access delay should not exceed from a maximum allowable threshold. Numerical results validate our proposed schemes and show that the total service time for the proposed method is very close to the optimal case where the information of the number of MTC devices is given.

Guest Editors’ Introduction to Special Issue on Advances in DSP System Design

The constant advances in IC technologies have introduced new challenges for implementations and design methodologies; higher integration level allows more complex systems to be implemented but on the other hand implementations often have strict constraints on power consumption. These challenges are present in signal processing systems implying the need to improve design methods and find more efficient algorithm-architecture optimizations. This special issue contains a selection of recent papers on design and implementation of signal processing systems ranging from circuit level architectures to scheduling methods and from application-specific architectures to implementations on many-core systems. In Data Center Switch for Load Balanced Fat-Trees, Lai, and Chiu demonstrate a fault tolerant switch IC operating at the maximum rate of 5.8 Gbps per channel. This work employs a load-balanced fat-tree architecture that does not consume all of its bandwidth even under heavy traffic. When there are broken links or faulty switches in the network even in heavy traffic load situations, available bandwidth remains in every connection pattern and alternative paths are provided to re-route the traffic. Fault tolerance capability evaluations of link or switch faults in the fattree network are given to support the presented idea, and a 4×4 Banyan type switch IC is developed as the commodity switch for building the fault tolerant fat-tree data center networks. Lee and Sung propose a cell-to-cell interference (CCI) cancellation technique for multi-level NAND flash memory in their paper Least Squares Based Coupling Cancellation for MLC NAND Flash Memory with a Small Number of Voltage Sensing Operations. Their two-step algorithm consists of training and then interference removal performed during the page read operation. A least-squares adaptive CCI canceller is developed and optimal quantization schemes are studied. Experimental results show a significant BER improvement despite a low number of voltage sensing operations. In A Fast Recursive Algorithm and Architecture for Pruned Bit-Reversal Interleavers, Mansour describes an algorithm and architecture for implementing interleavers used in communications applications such as errorcorrecting codes (turbo codes) and bit-interleaved coded modulation. A mathematical formulation for developing flexible-length interleavers is developed along with a study of permutation statistics. Practical examples of implementations of parallel interleavers are provided. In Highly Parallelable Bidimensional Median Filter for Modern Parallel Programming Models, Sanchez and Rodriguez present efficient parallel implementation methods for median filtering. The authors implement their previous work on the parallel ccdf-based median filter (PCMF) on a GPU (Graphics Processing Unit), and show that the proposed median filtering algorithm is efficient and can outperform other generic median filters for the GPU. The proposed algorithm is implemented in three parallel programming models: SIMD Intel, multi-core Intel with SIMD, and SIMT (CUDA). Additionally they make use of the salt & pepper noise model to improve the image reconstruction quality with a small performance impact. J. Takala (*) Department of Pervasive Computing, Tampere University of Technology, Tampere, Finland e-mail: jarmo.takala@tut.fi

An Energy-Efficient MAC Protocol with Probabilistic Scheduled Listen-Sleep Cycles for Wireless Sensor Networks

In this paper, we propose an energy efficient MAC protocol for wireless sensor networks. In sensor networks, reducing energy consumption is one of the critical issues for extending network lifetime. One good solution to resolve this issue is introducing listen-sleep cycles, allowing sensor nodes to turn their transceiver off during sleep periods, which was adopted by S-MAC [1]. However, in S-MAC, due to the synchronized scheduling, transmission collisions will increase in heavy traffic situations, resulting in energy waste and low throughput. Hence, in this paper, we propose probabilistic scheduled MAC (PS-MAC), in which each node determines ‘listen’ or ‘sleep’ pseudo-randomly based on its own pre-wakeup probability and pre-wakeup probabilities of its neighbor nodes in each time slot. This allows the listen-sleep schedule of nodes in each transmitter and receiver pair to be synchronized, while maintaining those of the rest of nodes to be asynchronous. Therefore, collisions can be reduced even under heavy traffic conditions, resulting in reduced energy waste and high throughput. In addition, by dynamically adjusting the pre-wakeup probabilities of sensor nodes based on the change of the network environment, system throughput and latency can be further improved. Simulation results show that PS-MAC provides significant energy savings, low delay, and high network throughput.

Small-world overlay P2P networks: Construction, management and handling of dynamic flash crowds

We consider how to construct and maintain a structured overlay P2P network based on the small-world paradigm. Two main attractive properties of a small-world network are (1) a low average hop distance between any two randomly chosen nodes, and (2) a high clustering coefficient. A network with a low average hop distance implies small latency for object lookup. A network with a high clustering coefficient implies the ability to provide efficient object lookup even under heavy object traffic loadings, such as in a flash crowd scenario. We present the SWOP protocol for constructing a small-world overlay P2P network. We compare our system's performance with other structured P2P networks, such as Chord. Whereas the Chord protocol already provides a scalable object lookup latency of O(log(N)), where N is the number of nodes in a P2P network, we show that the SWOP protocol can further improve the object lookup performance. We also take advantage of the high clustering coefficient of a small-world P2P network to design an object replication algorithm that can handle heavy object traffic loading situations. We show that the SWOP network can efficiently deliver popular, possibly dynamic, objects to all the requesting nodes. To the best of our knowledge, ours is the first work that addresses how to handle dynamic flash crowds in a structured P2P network.

Conceptual and Scaling Evaluation of Vehicle Traffic Thermal Effects on Snow/Ice-Covered Roads*

The potential thermal effects of traffic on road surface thermal energy balance under frost/snow cover conditions have been largely ignored in meteorological evaluations of road ice deposit conditions. Preliminary exploration of these effects, particularly for heavy traffic scenarios with calm wind conditions and an ambient temperature of 0°C, is provided in this study using a conceptual model. Observational data were used to constrain the model, and parameterizations were employed to estimate the various heat transfer processes involved. The results indicate that, for heavy traffic situations, as well as for stopped traffic at intersections, the traffic thermal flux contribution at the surface is noticeable in a wide range of possible frost/snow-covered road conditions. The sensitivity to variation in traffic density, speed, and the emissivity of vehicle radiative surfaces, among others, is evaluated. Simple quantification of these traffic thermal effects, which might be considered in operational meteorological model forecasting of icy road conditions, is offered.

Electronic flight progress strip prototype for en route ATC

An electronic flight progress strip (FPS) display and a color plan view display (CPVD) as a laboratory prototype are described. The purposes of prototype development are to examine the effectiveness and problems of the electronic FPS display in comparison to the current system and to identify the controller-workstation requirements, which are necessary to decide a future planning of a production prototype development. The evaluation and additional test were conducted for a typical en route transition sector. It was found that electronic FPS was useful in the normal traffic load. Some possible improvements were identified in the heavy traffic load situations represented in the additional test.

Simulation and theoretical results on cluster management and directory management in dynamic hierarchical networks

A cluster management scheme for dynamic networks, the purpose of which is to maintain the cluster structure of the hierarchical network as a balanced-tree topology is presented. The theoretical time complexity bounds of the cluster management scheme for node birth and death are derived. The effects of the cluster management on gate-connected fixed-node networks under heavy intercluster traffic situations are discussed. In order to show that the scheme can handle realistic communication networks, routing tables and OD pair shortest path routing are used. The settle-down time, throughput, and end-to-end link delays of a network that uses cluster management and a network of the same topology that only uses flooding are compared. >

Validating the heavy traffic performance of regenerative simulation

Following a theoretical study by Asmussen [2] indicating severe problems associated with a number of standard queueing simulation schemes in heavy traffic situations, we look into one of the possible settings of regenerative simulation from a more empirical point of view. Sequences of queues with are simulated subject to various growth rates of the sample size t:, the empirical distribution of a certain Brownian functional describing the heavy traffic limit of the regenerative estimator is exhibited and compared to that of the estimator itself, and finally similar experiments are performed for the regenerative variance estimator