Optimized design research of fully enclosed noise barrier

Fully enclosed noise barrier has been used to prevent and control traffic noise pollution because of its effectiveness. It has become the best solution for controlling environmental noise of high-rise buildings from expressways, urban viaducts and railways that cross the crowded downtown area. However, its high cost has become an important retarding factor on its application and popularization, so reducing the cost become an urgent problem. The research theory, structure frame, sound absorbing and insulating materials are investigated for the fully enclosed noise barrier, so as to provide technical solutions for optimizing the design scheme and reducing the construction cost.

Flow Sensing-Based Congestion Detection for D2D Streaming on a 5G gNB

To provide high-quality streaming services in device-to-device (D2D) communications, performance parameters such as encoding rate, decoding rate, and flow rate should be detected and monitored. The proposed algorithm provides a method to detect time streaming for traffic flows in D2D communications, and a sequence to detect rate imbalance. This paper proposes a new FS-CDA (flow sensing-based congestion detecting algorithm) to prevent high congestion rates and assist an optimized D2D streaming service in 5G-based wireless mobile networks. The proposed algorithm detects and controls flow imbalance for streaming segments during D2D communications, and it includes operations such as transmission rate monitoring, rate adjustment functions, and underflow and overflow sensing for these operations. The paper aims to effectively control traffic flow rates caused by adjacent channel bandwidth, high bit rate error, and heterogeneous radio interference, and to enhance the performance of D2D streaming services by performing such operations. The proposed algorithm for D2D streaming services is measured by deriving the individual weight of certain versions of a streaming flow. Based on the given operations, the simulation results indicated that the proposed algorithm has better performance with respect to average congestion control ratio, PSNR, and average throughput than other methods.

A review of computational intelligence methods for traffic management systems

One of the most important challenges in modern city life is to enable effective and efficient traffic management system. Recently, computational intelligence methods have become increasingly popular for traffic management system design, application, and monitoring. Computational intelligence methods are often deployed for managing traffic, that is for reducing mileage, congestion, the use of fuels, and environmental impact. The aim of this paper is twofold. First, to present the three main areas in a computational intelligence approach, namely neural networks, fuzzy logic systems, and evolutionary computation. Second, to emphasize their impact on various traffic management domains, including traffic flow forecasting, traffic light control, traffic fatalities prediction, traffic sign detection, and optimization of transportation networks.

A review of computational intelligence methods for traffic management systems

One of the most important challenges in modern city life is to enable effective and efficient traffic management system. Recently, computational intelligence methods have become increasingly popular for traffic management system design, application, and monitoring. Computational intelligence methods are often deployed for managing traffic, that is for reducing mileage, congestion, the use of fuels, and environmental impact. The aim of this paper is twofold. First, to present the three main areas in a computational intelligence approach, namely neural networks, fuzzy logic systems, and evolutionary computation. Second, to emphasize their impact on various traffic management domains, including traffic flow forecasting, traffic light control, traffic fatalities prediction, traffic sign detection, and optimization of transportation networks.

MIDET: A Method for Indexing Traffic Events

Traffic events announcements such as jams and road closures are continuously reported by mobile and Web applications. This collection of spatio-temporal data is an important source of information for urban planning, and can be used to orchestrate a number of actions to mprove the mobility, such as traffic control, traffic lights synchronization and preventive maintenance. Such analysis usually involves computation of spatial relationships among data, and may involve location of landmarks, roads and different types of events. In this paper, we propose a Method for Indexing Traffic Events (MIDET) for querying spatio-temporal data, whose location can be represented as a point or collection of points. MIDET is based on a fixed-grid space-oriented partitioning. In order to tackle the data skew, each grid cell is associated with a set of blocks containing event records. Moreover, a bitmap index is used for filtering out blocks without retrieving the actual data. MIDET provides the following benefits: adoption of a simple bulk loading process to manage dynamic insertion streams, and in-memory spatial joins. We conducted an experimental study using real data obtained from Waze. MIDET’s query performance was compared with Postgis, which adopts an R-tree index structure.

Structuring tasks of control over driverless vehicles within intelligent transport systems

The relevance of the research topic is defined by the global level of significance of the problem of creation and safe operation of driverless transport on public roads. The research objective was to develop a mathematical model of the problem that allows forming a scientifically grounded strategy for driverless transport progress. The Zwicky Morphological Box method was used as a research method, which allowed building a structured set of intelligent transport system variants. Variables corresponding to the hard-surfaced road types, the level of informational support in the form of digital road models and the level of control tasks with increasing complexity were used as structural variables. A complex of tasks required to control traffic or driving in closed territories, on highways, suburban motorways passing through human settlements, urban streets, and yards has been defined. The control task complexes of each consecutive level include the task complexes of all the previous levels, and the digital road models of a higher level contain the digital models of all the previous levels. The analysis of the obtained results allowed building a trajectory of progressive development of the driverless vehicle focus area within the field of control task levels, road types, and their digital models.

Vehicle Detection and Traffic Prediction

On the road, vehicle detection processes are utilized for vehicle tracking, vehicle counting, vehicle speed, and traffic analysis. For vehicle detection, the Tensorflow object detection API method is employed. The Object Detection API in Tensorflow is a powerful tool that allows anyone to easily design and deploy effective picture recognition applications. Another way to control traffic is to use a traffic control system. Multiple linear regression is utilized to regulate the traffic system, while the OpenCV approach is used to identify vehicle speed. A system for fine payment is also offered. It makes police officers' jobs easier. The exact results of vehicle speed and traffic control are provided. Keywords: Vehicle detection, Tensorflow object detection API, Multiple linear regression, OpenCV, Fine payment

Congestion Control for Medical Emergency with Vehicle-to-Vehicle Communication Using IoT

Traffic is a huge trouble which takes place after an accident. Vehicles in the accident area get congested, moreover without knowing about the accident, vehicles coming from the other roads make the situation difficult for the ambulance to travel and reach the nearest hospital on time. So keeping those problems in mind, an approach that will be able to avoid series of collision and also can control traffic jam using vehicle to vehicle communication.