Portable optical fiber Bragg grating sensor for monitoring traffic density

The paper examines the development of a portable sensor strip with fiber optic Bragg grating for monitoring urban traffic density up to 80 kph. It contains a 2.5-m-long and a 2-cm-high sensor created from a combination of silicone addition rubber (bicomponent addition silicone rubber) and Bragg grating placed inside a carbon tube. The design of the portable sensor permits traffic density and cars crossings to be monitored and detected in a single lane. The functionality of the sensor was verified in real traffic; the results of this study are based on the detection of 1518 vehicles of different types and sizes. According to the measurements, the sensor is characterized by a high detection rate of 98.946%.Web of Science922art. no. 479

Vehicle classification in intelligent transport systems: an overview, methods and software perspective

Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS). Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet monitoring, traffic safety, and automated parking are using VC. Basically, in the current VC methods, vehicles are classified locally as a vehicle passes through a monitoring area, by fixed sensors or using a compound method. This paper presents a pervasive study on the state of the art of VC methods. We introduce a detailed VC taxonomy and explore the different kinds of traffic information that can be extracted via each method. Subsequently, traditional and cutting edge VC systems are investigated from different aspects. Specifically, strengths and shortcomings of the existing VC methods are discussed and real-time alternatives like Vehicular Ad-hoc Networks (VANETs) are investigated to convey physical as well as kinematic characteristics of the vehicles. Finally, we review a broad range of soft computing solutions involved in VC in the context of machine learning, neural networks, miscellaneous features, models and other methods

Strain Distribution and Crack Detection in Concrete Overlays with Pulse Pre-Pump Brillouin Optical Time Domain Analysis

This report is focused on the measurement of strain distributions and crack detection in unbonded and bonded pavement overlays. The main objectives of this study are: (a) to characterize the strain sensing properties of distributed fiber optic sensors with recently developed pulse pre-pump Brillouin optical time domain analysis (PPP-BOTDA), (b) to develop an installation method for real world applications, (c) to document the performance of the PPP-BOTDA technology in unbonded/bonded pavement applications, and (d) to develop a numerical model to facilitate the analysis of mechanical behavior of unbonded pavement overlay under vehicle wheel loads. A thin concrete layer can be cast on top of a severely deteriorated pavement layer with a fabric sheet in between to rapidly and cost effectively improve the driving condition of existing roadways. Once cured, the concrete layer is divided into many panels and often referred to as the unbonded Portland cement concrete (PCC) overlay. The service life of PCC overlays can be appreciably extended by appropriate rehabilitation strategies at early stages of deterioration based on the information provided by health monitoring. The strain distribution and crack detection are of interest to engineers in this application. Minor or moderately deteriorated existing concrete pavements can also be resurfaced with a thin concrete layer to improve their driving condition. In this case, potential cracks in the existing pavement may easily penetrate through the new concrete layer. The way the potential slip at their interface develops over time is an interesting question to answer. This study reports an application of a commercial single mode optical fiber to measure strain distributions in full-scale fiber reinforced unbonded overlays. Prefabricated cementitious mortar grid instrumented with distributed fiber optic sensors, namely smart grid, was developed and proposed to address the logistics of handling delicate optical fibers, and thus facilitate the in-situ construction. The smart grids can be laid on top of the fabric sheet and embedded in concrete overlay. With the proposed method, the pavement overlays instrumented with distributed sensors were successfully constructed in Minnesota\u27s Cold Weather Road Research Facility (MnROAD). The optical fibers were characterized on a precision load frame at room temperature. A Neubrescope was used to measure strain distributions based on the pulse pre-pump Brillouin optical time domain analysis (PPPBOTDA). The overlays were subjected to repeated truck loads and eventually cracked. Strain distributions were obtained from the distributed fiber optic sensor. Cracks were identified and localized by mapping the strain distribution in which the sharp peaks represent the cracks. The strain distribution was further investigated using a three-dimensional finite element model incorporating nonlinear boundary conditions. Opening between substrate and overlay concrete was demonstrated, and strain distributions in overlay and substrate concrete were determined with the numerical model. For the bonded concrete overlays on existing pavement, a delamination detection method was developed and implemented using the distributed fiber optic sensors. Delamination can be identified as sharp peaks in the measured strain distributions

A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials

Smart materials are promising technologies for reducing the instrumentation cost required to continuously monitor road infrastructures, by transforming roadways into multifunctional elements capable of self-sensing. This study investigates a novel algorithm empowering smart pavements with weigh-in-motion (WIM) characterization capabilities. The application domain of interest is a cementitious-based smart pavement installed on a bridge over separate sections. Each section transduces axial strain provoked by the passage of a vehicle into a measurable change in electrical resistance arising from the piezoresistive effect of the smart material. The WIM characterization algorithm is as follows. First, basis signals from axles are generated from a finite element model of the structure equipped with the smart pavement and subjected to given vehicle loads. Second, the measured signal is matched by finding the number and weights of appropriate basis signals that would minimize the error between the numerical and measured signals, yielding information on the vehicle’s number of axles and weight per axle, therefore enabling vehicle classification capabilities. Third, the temporal correlation of the measured signals are compared across smart pavement sections to determine the vehicle weight. The proposed algorithm is validated numerically using three types of trucks defined by the Eurocodes. Results demonstrate the capability of the algorithm at conducting WIM characterization, even when two different trucks are driving in different directions across the same pavement sections. Then, a noise study is conducted, and the results conclude that a given smart pavement section operating with less than 5% noise on measurements could yield good WIM characterization results

Perpetual Pavement Instrumentation for the Marquette Interchange Project-Phase 1

This report provides details on the design, installation and monitoring of a pavement instrumentation system for the analysis of load-induced stresses and strains within a perpetual HMA pavement system. The HMA pavement was constructed as part of an urban highway improvement project in the City of Milwaukee, Wisconsin. The outer wheel path of the outside lane was instrumented with asphalt strain sensors, base and subgrade pressure sensors, subgrade moisture and temperature sensors, HMA layer temperature sensors, traffic wander strips and a weigh in motion system. Environmental sensors for air temperature, wind speed and solar radiation are also included. The system captures the pavement response from each axle loading and transmits the data through a wireless link to a resident database at Marquette University. The collected data will be used to estimate the fatigue life of the perpetual HMA pavement and to modify, as necessary, pavement design procedures used within the State of Wisconsin

Marquette Interchange Phase I Final Report

This report provides details on the design, installation and monitoring of a pavement instrumentation system for the analysis of load-induced stresses and strains within a perpetual HMA pavement system. The HMA pavement was constructed as part of an urban highway improvement project in the City of Milwaukee, Wisconsin. The outer wheel path of the outside lane was instrumented with asphalt strain sensors, base and subgrade pressure sensors, subgrade moisture and temperature sensors, HMA layer temperature sensors, traffic wander strips and a weigh in motion system. Environmental sensors for air temperature, wind speed and solar radiation are also included. The system captures the pavement response from each axle loading and transmits the data through a wireless link to a resident database at Marquette University. The collected data will be used to estimate the fatigue life of the perpetual HMA pavement and to modify, as necessary, pavement design procedures used within the State of Wisconsin

Fiber Bragg Grating Based Sensors and Systems

This book is a collection of papers that originated as a Special Issue, focused on some recent advances related to fiber Bragg grating-based sensors and systems. Conventionally, this book can be divided into three parts: intelligent systems, new types of sensors, and original interrogators. The intelligent systems presented include evaluation of strain transition properties between cast-in FBGs and cast aluminum during uniaxial straining, multi-point strain measurements on a containment vessel, damage detection methods based on long-gauge FBG for highway bridges, evaluation of a coupled sequential approach for rotorcraft landing simulation, wearable hand modules and real-time tracking algorithms for measuring finger joint angles of different hand sizes, and glaze icing detection of 110 kV composite insulators. New types of sensors are reflected in multi-addressed fiber Bragg structures for microwave–photonic sensor systems, its applications in load-sensing wheel hub bearings, and more complex influence in problems of generation of vortex optical beams based on chiral fiber-optic periodic structures. Original interrogators include research in optical designs with curved detectors for FBG interrogation monitors; demonstration of a filterless, multi-point, and temperature-independent FBG dynamical demodulator using pulse-width modulation; and dual wavelength differential detection of FBG sensors with a pulsed DFB laser

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques

A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques

Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques

Nondestructive fiber optic sensor system for measurement of traffic speed

Disertační práce popisuje návrh, realizaci a otestování nového způsobu detekce a měření rychlosti vozidel s primárním zaměřením na silniční provoz do rychlosti 100km/h, který lze využít v koncepci SMART Cities. Uvedené výsledky v této práci potvrzují, že podobný přístup lze využít rovněž pro monitorování tramvajového provozu, provozu metra a vlakových souprav na železnici. Popsaný měřicí systém je založen na využití interference v optických vláknech. Základem řešení je sériové zapojení senzorických jednotek na bázi Mach-Zehnderova interferometru pracujících s jednovidovými telekomunikačními optickými vlákny standardu G.652.D. a G.653, vlnovou délkou 1550nm a nároky na výkon zdroje záření v řádech jednotek mW. Řešení popsaná v této disertační práci jsou v současné době chráněna autorským osvědčením (patent číslo 306992). Základem tohoto řešení je imunita vůči elektromagnetickým interferencím (EMI) a jednoduchá implementace, protože senzorické jednotky není nutné instalovat destruktivně do vozovky nebo kolejiště. Vzhledem k masivnímu rozšíření optických kabelů podél silnic a železničních tratí, které zabezpečují telekomunikační a bezpečnostní služby, je významnou výhodou i možnost přímého napojení senzorů na stávající infrastrukturu a možnost vzdáleného vyhodnocení. Měřicí systém byl dlouhodobě testován v reálném provozu a je charakterizován chybou v toleranci ± 3km/h udávané u úsekových měřicích systémů do rychlosti 100km/h v České republice.My dissertation thesis describes a design, implementation, and testing of a new way of vehicles detection and speed measurement primarily used in the road transport with the speed limit up to 100kph, which can be utilized in the concept of SMART Cities. Results published in this thesis confirm that a similar approach can be also used for the monitoring of tram, underground and railway transport. The proposed measuring system is based on the interference in optical fibers. The key condition is that sensory units are connected in series on the basis of Mach-Zehnder interferometer working with single-mode optical fibers of G.652.D. and G.653 standards, with the wavelength of 1550nm and demands on the radiation source output in the range of mW. Solutions described in this dissertation thesis are currently protected by copyright (the patent No.306992). The basis of this solution lies in electromagnetic interference immunity (EMI) and simple implementation as the sensory units do not need to be installed destructively into the roadway or railway. With regard to a massive use of optical fibers along roads and railway tracks, which provides telecommunications and security services, the important advantage is also the possibility of direct connections of sensors to existing infrastructure and the possibility of remote evaluation. The measuring system was tested in real traffic over a long period and is characterized by an error with the tolerance of ± 3kph which is given by sectional speed measuring systems up to 100kph in the Czech Republic.440 - Katedra telekomunikační technikyvyhově