Search results for: remote traffic microwave sensor

Authors: Z. Ezzouine, A. Nakheli

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This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: electromagnetic sensor, accurately, data acquisition, position measurement

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Authors: Shathya Duobiene, Gediminas Račiukaitis

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Solar-powered wireless sensor nodes work best when they operate continuously with minimal energy consumption. Wireless Sensor Networks (WSNs) are a new technology opens up wide studies, and advancements are expanding the prevalence of numerous monitoring applications and real-time aid for environments. The Selective Surface Activation Induced by Laser (SSAIL) technology is an exciting development that gives the design of WSNs more flexibility in terms of their shape, dimensions, and materials. This research work proposes a methodology for using SSAIL technology for forest ecosystem monitoring by wireless sensor networks. WSN monitoring the temperature and humidity were deployed, and their architectures are discussed. The paper presents the experimental outcomes of deploying newly built sensor nodes in forested areas. Finally, a practical method is offered to extend the WSN's lifespan and ensure its continued operation. When operational, the node is independent of the base station's power supply and uses only as much energy as necessary to sense and transmit data.

Keywords: internet of things (IoT), wireless sensor network, sensor nodes, SSAIL technology, forest ecosystem

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Authors: Van Nhan Nguyen, Harald Holone

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Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: automatic speech recognition, asr, air traffic control, atc

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Authors: Amri Yusoff, Shahrizuan Shafiril, Ashardi Abas, Norma Che Yusoff

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Nowadays, illegal logging has been causing much effect to our forest. Some of it causes a flash flood, avalanche, global warming, and etc. This comprehensibly makes us wonder why, what, and who has made it happened. Often, it already has been too late after we have known the cause of it. Even the Malaysian Royal Belum forest has not been spared from land clearing or illegal activity by the natives although this area has been gazetted as a protected area preserved for future generations. Furthermore, because of its sizeable and wide area, these illegal activities are difficult to monitor and to maintain. A critical action must be called upon to prevent all of these unhealthy activities from recurrence. Therefore, a remote monitoring device must be developed in order to capture critical real-time data such as temperature, humidity, gaseous, fire, and rain detection which indicates the current and preserved natural state and habitat in the forest. Besides, this device location can be detected via GPS by showing the latitudes and longitudes of its current location and then to be transmitted by SMS via GSM system. All of its readings will be sent in real-time for data management and analysis. This result will be benefited to the monitoring bodies or relevant authority in keeping the forest in the natural habitat. Furthermore, this research is to gather a unified data and then will be analysed for its comparison with an existing method.

Keywords: remote monitoring system, forest data, GSM, GPS, wireless sensor

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Authors: Khaled A. Alsaif, Mosaad A. Foda

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The present work aims at development of traffic noise maps for Riyadh City using the software Lima. Road traffic data were estimated or measured as accurate as possible in order to obtain consistent noise maps. The predicted noise levels at some selected sites are validated by actual field measurements, which are obtained by a system that consists of a sound level meter, a GPS receiver and a database to manage the measured data. The maps show that noise levels remain over 50 dBA and can exceed 70 dBA at the nearside of major roads and highways.

Keywords: noise pollution, road traffic noise, LimA predictor, GPS

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Authors: Hayrettin Eroglu, Adem Kara

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Recently there has been significant attention given to imaging of the biological tissues via microwave imaging techniques. In this study, a phantom for the test and calibration of Microwave imaging used in detecting unhealthy breast structure or tumors was produced by using sol gel method. The liquid and gel phantoms being used nowadays are not durable due to evaporation and their organic ingredients, hence a new design was proposed. This phantom was fabricated from materials that were widely available (water, salt, gelatin, and glycerol) and was easy to make. This phantom was aimed to be better from the ones already proposed in the literature in terms of its durability and stability. S Parameters of phantom was measured with 1-18 GHz Probe Kit and permittivity was calculated via Debye method in “85070” commercial software. One, three, and five-week measurements were taken for this phantom. Finally, it was verified that measurement results were very close to the real biological tissue measurement results.

Keywords: phantom, breast tissue, cancer, microwave imaging

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Authors: Spoorthi Srupad

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Environmental Impact Assessment (EIA) stands as a critical engineering application facilitated by Earth Resources and Environmental Remote Sensing. Employing advanced technologies, this process enables a systematic evaluation of potential environmental impacts arising from engineering projects. Remote sensing techniques, including satellite imagery and geographic information systems (GIS), play a pivotal role in providing comprehensive data for assessing changes in land cover, vegetation, water bodies, and air quality. This abstract delves into the significance of EIA in engineering, emphasizing its role in ensuring sustainable and environmentally responsible practices. The integration of remote sensing technologies enhances the accuracy and efficiency of impact assessments, contributing to informed decision-making and the mitigation of adverse environmental consequences associated with engineering endeavors.

Keywords: environmental impact assessment, engineering applications, sustainability, environmental monitoring, remote sensing, geographic information systems, environmental management

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Authors: Seyed Mohsen Jameii

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Wireless underwater sensor networks are a type of sensor networks that are located in underwater environments and linked together by acoustic waves. The application of these kinds of network includes monitoring of pollutants (chemical, biological, and nuclear), oil fields detection, prediction of the likelihood of a tsunami in coastal areas, the use of wireless sensor nodes to monitor the passing submarines, and determination of appropriate locations for anchoring ships. This paper proposes a boundary coverage algorithm for intrusion detection in underwater sensor networks. In the first phase of the proposed algorithm, optimal deployment of nodes is done in the water. In the second phase, after the employment of nodes at the proper depth, clustering is executed to reduce the exchanges of messages between the sensors. In the third phase, the algorithm of "divide and conquer" is used to save energy and increase network efficiency. The simulation results demonstrate the efficiency of the proposed algorithm.

Keywords: boundary coverage, clustering, divide and ‎conquer, underwater sensor nodes

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Authors: Gagandeep Singh, Navdeep Singh

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Due to limited battery of sensor nodes, so energy efficiency found to be main constraint in WSN. Therefore the main focus of the present work is to find the ways to minimize the energy consumption problem and will results; enhancement in the network stability period and life time. Many researchers have proposed different kind of the protocols to enhance the network lifetime further. This paper has evaluated the issues which have been neglected in the field of the WSNs. WSNs are composed of multiple unattended ultra-small, limited-power sensor nodes. Sensor nodes are deployed randomly in the area of interest. Sensor nodes have limited processing, wireless communication and power resource capabilities Sensor nodes send sensed data to sink or Base Station (BS). I-LEACH gives adaptive clustering mechanism which very efficiently deals with energy conservations. This paper ends up with the shortcomings of various adaptive clustering based WSNs protocols.

Keywords: WSN, I-Leach, MATLAB, sensor

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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Traffic calming measures are different design features or strategies used to reduce the speed of a traveling vehicle on a particular road. These calming measures are common on rural roads of Oman. Some of these measures are road speed limits, vertical deflections, horizontal deflections, and road signs. In general, vertical deflections such as rumble strips, road studs (cat’s eye), speed tables, and speed humps are widely used. In this paper, as vehicle speeding is a major cause of road traffic crashes and high fatalities in Oman, the effectiveness of existing traffic calming measures at current locations on rural roads is assessed. The study was conducted on the rural roads of Dhofar Governorate, which is located in the south of Oman. A special focus is given to the calming measures implemented on the mountain roads of Dhofar. It is shown that vertical deflection calming measures are effective in reducing vehicle speed to 20 to 40 kph, depending on the vertical deflection type and spacing. Calming measures are also proposed at locations with a high probability of traffic crashes based on the number of traffic crashes at these locations, road type, and road geometry.

Keywords: road safety, rural roads, speed, traffic calming measures, traffic crash

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Authors: Li Long, Thomas Ortlepp

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A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

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Authors: Elmabruk Laias, Abdalla M. Hanashi, Mohammed Alnas

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Worldwide Interoperability for Microwave Access (WiMAX) became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, the proposed algorithm focuses on an efficient mechanism to serve non-real time traffic in congested networks by considering channel status.

Keywords: WiMAX, Quality of Services (QoS), OPNE, Diff-Serv (DS).

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Authors: Ehsan Abdolzadeh, Sanaz Nouri, Siamak Khalaj

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Today WSNs have many applications in different fields like the environment, military operations, discoveries, monitoring operations, and so on. Coverage size and energy consumption are the important challenges that these networks need to face. This paper tries to solve the problem of coverage with a requirement of k-coverage and minimum energy consumption. In order to minimize energy consumption, visual sensor networks have been used that observe and process just those targets that are located in their view direction. As a result, sensor rotations have decreased, and subsequently, energy consumption has been minimized. To solve the problem of coverage particle swarm optimization, coverage optimization has been able to ensure coverage requirement together with minimizing sensor rotations while meeting the problem requirement of k≤14. So energy consumption has decreased, and this could extend the sensors’ lifetime subsequently.

Keywords: K coverage, particle union optimization algorithm, wireless sensor networks, visual sensor networks

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Authors: Kashish Sareen, Jatinder Singh Bal

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The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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Authors: Bojan Najdenov, Danco Davcev

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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

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Authors: Tuğçe Yücel

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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Manoj Kumar

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper, we compare AODV, DSDV, DSR, and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyze these routing protocols by extensive simulations in OPNET simulator and show how to pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, sent data traffic, throughput, retransmission attempts.

Keywords: AODV, DSDV, DSR, ZRP

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Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

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A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

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Authors: Mohammad Reza Taherkhani‎

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make a connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: underwater sensor networks, clustering, learning automata, energy consumption

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Authors: Issam Derkaoui, Mohammed Khenfouch, Bakang M. Mothudi, Malik Maaza, Izeddine Zorkani, Anouar Jorio

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Transition metal oxides nanoparticles with different morphologies have attracted a lot of attention recently owning to their distinctive geometries, and demonstrated promising electrical properties for various applications. In this paper, we discuss the time and annealing effects on the structural and electrical properties of vanadium oxides nanoparticles (VO-NPs) prepared by microwave method. In this sense, transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman Spectroscopy, Ultraviolet-visible absorbance spectra (Uv-Vis) and electrical conductivity were investigated. Hence, the annealing state and the time are two crucial parameters for the improvement of the optoelectronic properties. The use of these nanostructures is promising way for the development of technological applications especially for energy storage devices.

Keywords: Vanadium oxide, Microwave, Electrical conductivity, Optoelectronic properties

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Authors: Spoorthi Sripad

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Rapid advancements in LiDAR (Light Detection and Ranging) technology, coupled with the synergy of remote sensing, have revolutionized Earth observation methodologies. This paper delves into the transformative impact of integrated LiDAR and remote sensing systems. Focusing on miniaturization, cost reduction, and improved resolution, the study explores the evolving landscape of terrestrial and aquatic environmental monitoring. The integration of multi-wavelength and dual-mode LiDAR systems, alongside collaborative efforts with other remote sensing technologies, presents a comprehensive approach. The paper highlights the pivotal role of LiDAR in environmental assessment, urban planning, and infrastructure development. As the amalgamation of LiDAR and remote sensing reshapes Earth observation, this research anticipates a paradigm shift in our understanding of dynamic planetary processes.

Keywords: LiDAR, remote sensing, earth observation, advancements, integration, environmental monitoring, multi-wavelength, dual-mode, technology, urban planning, infrastructure, resolution, miniaturization

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Authors: Andrew Randles, Ilker Ocak, Cheam Daw Don, Navab Singh, Alex Gu

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Nine Degrees of Freedom (9 DOF) systems are already in development in many areas. In this paper, an integrated pressure sensor is proposed that will make use of an already existing monolithic 9 DOF inertial MEMS platform. Capacitive pressure sensors can suffer from limited sensitivity for a given size of membrane. This novel pressure sensor design increases the sensitivity by over 5 times compared to a traditional array of square diaphragms while still fitting within a 2 mm x 2 mm chip and maintaining a fixed static capacitance. The improved design uses one large diaphragm supported by pillars with fixed electrodes placed above the areas of maximum deflection. The design optimization increases the sensitivity from 0.22 fF/kPa to 1.16 fF/kPa. Temperature sensitivity was also examined through simulation.

Keywords: capacitive pressure sensor, 9 DOF, 10 DOF, sensor, capacitive, inertial measurement unit, IMU, inertial navigation system, INS

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: Khelifa Benahmed, Tarek Benahmed

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There are diverse applications of wireless sensor networks (WSNs) in the real world, typically invoking some kind of monitoring, tracking, or controlling activities. In an application, a WSN is deployed over the area of interest to sense and detect the events and collect data through their sensors in a geographical area and transmit the collected data to a Base Station (BS). This paper presents an overview of the research solutions available in the field of environmental monitoring applications, more precisely the problems of critical area monitoring using wireless sensor networks.

Keywords: critical infrastructure monitoring, environment monitoring, event region detection, wireless sensor networks

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Authors: Wai Keng Teng, Gek Cheng Ngoh, Rozita Yusoff, Mohamed Kheireddine Aroua

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As a by-product of the biodiesel industries, glycerol has been vastly generated which surpasses the market demand. It is imperative to develop an efficient glycerol valorization processes in minimizing the net energy requirement and intensifying the biodiesel production. In this study, base-catalyzed transesterification of glycerol with dimethyl carbonate using microwave irradiation as heating method to produce glycerol carbonate was conducted by varing grades of glycerol i.e. 70%, 86% and 99% purity that obtained from biodiesel plant. Metal oxide catalysts were used with varying operating parameters including reaction time, DMC/glycerol molar ratio, catalyst weight %, temperature and stirring speed. From the study on the effect of different operating parameters; it was found that the type of catalyst used has the most significant effect on the transesterification reaction. Admist the metal oxide catalysts examined, CaO gave the best performance. This study indicates the feasibility of producing glycerol carbonate using different grade of glycerol in both conventional thermal activation and microwave irradiation with CaO as catalyst. Microwave assisted transesterification (MAT) of glycerol into glycerol carbonate has demostrated itself as an energy efficient route by achieving 94.3% yield of GC at 65°C, 5 minutes reaction time, 1 wt% CaO and DMC/glycerol molar ratio of 2. The advantages of MAT transesterification route has made the direct utilization of bioglycerol from biodiesel production without the need of purification. This has marked a more economical and less-energy intensive glycerol carbonate synthesis route.

Keywords: base-catalyzed transesterification, glycerol, glycerol carbonate, microwave irradiation

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

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In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

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Authors: Ghazwan Al-Haji

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Most accidents occur in urban areas, and the most related casualties are vulnerable road users (pedestrians and cyclists). The traffic calming measures (TCMs) are widely used and considered to be successful in reducing speed and traffic volume. However, TCMs create unwanted effects include: noise, emissions, energy consumption, vehicle delays and emergency response time (ERT). Different vertical and horizontal TCMs have been already applied nationally (Sweden) and internationally with different impacts. It is a big challenge among traffic engineers, planners, and policy-makers to choose and priorities the best TCMs to be implemented. This study will assess the existing guidelines for TCMs in relation to safety and ERT with focus on data from Norrkoping city in Sweden. The expected results will save lives, time, and money on particularly Swedish Roads. The study will also review newly technologies and how they can improve safety and reduce ERT.

Keywords: traffic calming measures, traffic safety, delay time, vulnerable road users

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Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.

Keywords: speed, Kriging, arterial, traffic volume

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