A Simulation Framework for Traffic Safety with Connected Vehicles and V2X Technologies

With the advancement in automobile technologies, existing research shows that connected vehicle (CV) technologies can provide better traffic safety through Surrogate Safety Measure (SSM). CV technologies involves two network systems: traffic network and wireless communication network. We found that the research in the wireless communication network for CV did not interact properly with the research in SSM in transportation network, and vice versa. Though various SSM has been proposed in previous studies, a few of them have been tested in simulation software in limited extent. On the other hand, A large body of researchers proposed various communication architecture for CV technologies to improve communication performance. However, none of them tested the advanced SSM in their proposed architecture. Hence, there exists a research gap between these two communities, possibly due to difference in research domain. In this study, we developed a V2X simulation framework using SUMO, OMNeT++ and Veins for the development and testing of various SSM algorithms in run time simulation. Our developed framework has three level of communication ( CV to RSU To TS) system and is applicable for large traffic network that can have mixed traffic system (CV and non-CV), multiple road side unit (RSUs), and traffic server (TS). Moreover, the framework can be used to test SSM algorithms for other traffic networks without doing much modification. Our developed framework will be publicly available for its further development and optimization

Use of Machine Learning and Natural Language Processing to Enhance Traffic Safety Analysis

Despite significant advances in vehicle technologies, safety data collection and analysis, and engineering advancements, tens of thousands of Americans die every year in motor vehicle crashes. Alarmingly, the trend of fatal and serious injury crashes appears to be heading in the wrong direction. In 2021, the actual rate of fatalities exceeded the predicted rate. This worrisome trend prompts and necessitates the development of advanced and holistic approaches to determining the causes of a crash (particularly fatal and major injuries). These approaches range from analyzing problems from multiple perspectives, utilizing available data sources, and employing the most suitable tools and technologies within and outside traffic safety domain.The primary source for traffic safety analysis is the structure (also called tabular) data collected from crash reports. However, structure data may be insufficient because of missing information, incomplete sequence of events, misclassified crash types, among many issues. Crash narratives, a form of free text recorded by police officers to describe the unique aspects and circumstances of a crash, are commonly used by safety professionals to supplement structure data fields. Due to its unstructured nature, engineers have to manually review every crash narrative. Thanks to the rapid development in natural language processing (NLP) and machine learning (ML) techniques, text mining and analytics has become a popular tool to accelerate information extraction and analysis for unstructured text data. The primary objective of this dissertation is to discover and develop necessary tools, techniques, and algorithms to facilitate traffic safety analysis using crash narratives. The objectives are accomplished in three areas: enhancing data quality by recovering missed crashes through text classification, uncovering complex characteristics of collision generation through information extraction and pattern recognition, and facilitating crash narrative analysis by developing a web-based tool. At first, a variety of NoisyOR classifiers were developed to identify and investigate work zone (WZ), distracted (DD), and inattentive (ID) crashes. In addition, various machine learning (ML) models, including multinomial naive bayes (MNB), logistic regression (LGR), support vector machine (SVM), k-nearest neighbor (K-NN), random forest (RF), and gated recurrent unit (GRU), were developed and compared with NoisyOR. The comparison shows that NoisyOR is simple, computationally efficient, theoretically sound, and has one of the best model performances. Furthermore, a novel neural network architecture named Sentence-based Hierarchical Attention Network (SHAN) was developed to classify crashes and its performance exceeds that of NoisyOR, GRU, Hierarchical Attention Network (HAN), and other ML models. SHAN handled noisy or irrelevant parts of narratives effectively and the model results can be visualized by attention weight. Because a crash often comprises a series of actions and events, breaking the chain of events could prevent a crash from reaching its most dangerous stage. With the objectives of creating crash sequences, discovering pattern of crash events, and finding missing events, the Part-of-Speech tagging (PT), Pattern Matching with POS Tagging (PMPT), Dependency Parser (DP), and Hybrid Generalized (HGEN) algorithms were developed and thoroughly tested using crash narratives. The top performer, HGEN, uses predefined events and event-related action words from crash narratives to find new events not captured in the data fields. Besides, the association analysis unravels the complex interrelations between events within a crash. Finally, the crash information extraction, analysis, and classification tool (CIEACT), a simple and flexible online web tool, was developed to analyze crash narratives using text mining techniques. The tool uses a Python-based Django Web Framework, HTML, and a relational database (PostgreSQL) that enables concurrent model development and analysis. The tool has built-in classifiers by default or can train a model in real time given the data. The interface is user friendly and the results can be displayed in a tabular format or on an interactive map. The tool also provides an option for users to download the word with their probability scores and the results in csv files. The advantages and limitations of each proposed methodology were discussed, and several future research directions were outlined. In summary, the methodologies and tools developed as part of the dissertation can assist transportation engineers and safety professionals in extracting valuable information from narratives, recovering missed crashes, classifying a new crash, and expediting their review process on a large scale. Thus, this research can be used by transportation agencies to analyze crash records, identify appropriate safety solutions, and inform policy making to improve highway safety of our transportation system

On relations of anisotropy and linear inhomogeneity using Backus average, 1-D tomography and two-parameter velocity inversion

We divide this thesis into three major parts. In the first part, we study three velocity models and corresponding traveltimes to obtain the inhomogeneity and anisotropy of a medium by comparing them to the field data. We derive an analytical relation that relates the linear inhomogeneity of a layered medium to the anisotropy parameter in an equivalent medium. For the analytic ease, we consider the P and S wave velocity gradients to be equal. We relax this constraint in the third part of the thesis, where the velocity gradients are independent of each other. We find that the obtained value of the anisotropy in the equivalent medium is in the same order of magnitude as the inhomogeneity parameter from the linearly inhomogeneous and elliptically anisotropic medium. This statement encourages us to do further investigation on the more general relationship between the inhomogeneity and anisotropy parameters in an equivalent medium. In the second part, we develop a 1-D traveltime tomography method to calculate the velocity of a medium. We use the results of 1-D tomography to obtain linear inhomogeneity parameters in a specific layer. To get the trustworthiness of the method, we perform several synthetic experiments. We show that the inverted model parameters are reasonably accurate and stable. To examine the results of linear inhomogeneity parameters using a different method, we also develop an inversion method based on a two-parameter velocity model. Finally, we apply both the methods to Vertical Seismic Profile (VSP) data and do a study comparing their results. In the third part, we derive an analytical relationship between the anisotropy, characterized by the Thomsen [1986] parameters, and the linear inhomogeneity parameters, which forms a system of three equations for nine unknowns. To obtain well-posedness, we constrain the problem by considering two seismological methods, 1-D tomography and two-parameter methods, applied to field data. Lastly, we compare the results that come from the application of each method to the analytical relationship, for a particular region of interest, to assess the validity of the theoretical relationship

Polypropylene melt-blown for electromagnetic shielding purposes

Protože se elektrické a elektronické přístroje a příslušenství rychle vyvíjejí, je důležité přenášet elektromagnetickou energii prostřednictvím různých frekvenčních pásem používaných na trzích, omezovat a zabránit elektronickým zařízením ze všech zdrojů rušení. Štíty se často používají k izolaci z místnosti, zařízení, obvodu atd. Zdroje elektromagnetického záření externě nebo k zamezení škodlivých vnitřních emisí elektromagnetické energie. Jedním z hlavních problémů se zavedením elektrické a elektronické technologie ve světě je elektromagnetické rušení mezi zařízeními. Různí vědci a průmyslové podniky se intenzivně zajímali o řešení tohoto problému. Tabule jsou tradičně považovány za nejlepší elektromagnetický stínící materiál, ale jsou drahé, těžké, flexibilní a tepelně expandované. Používání elektronických a elektrických zařízení textilních předmětů je však vhodné, protože jsou lehké, univerzální a levnější. Vědci upozornili na různá řešení, včetně textilních výrobků a kompozitních textilií, které tyto textilní struktury zahrnují flexibilitu a shodu. Nežádoucí elektromagnetická emise v kombinaci se specifickým zdrojem záření EMI nebo přenos do okolního elektrického systému jsou elektrické signály. Tento šum, části cívek, digitální zařízení a dlouhé kabely stejnosměrného nebo střídavého proudu mohou být způsobeny elektromagnety. Při frekvencích, které mohou vysílat energii na rádiové frekvenci [1]. Feromagnetické materiály ve směsi s vlákny a textiliemi jsou nakonec elektricky vodivé a účinné při ochraně před elektromagnetickým zářením. Pro elektromagnetické stínění se stříbro, měď nebo nerezová ocel nejlépe kombinují se střižovými nebo filamentovými vlákny. Pro různé elektromagnetické stínění tkaniny kompozitní příze vyrobené ze směšování kovových a textilních vláken. Tkaní kovových přízí je více obtížné než kompozitních přízí. Vedení polymerních kompozitů může vytvořit lepší funkčnost. Navíc je kovové potahování netkaných textilií pro komerční použití nákladově efektivní. Tato práce popisuje studii vývoje kovového povlaku na netkané textilii pro účely elektromagnetického stínění.As electric and electronic devices and accessories are increasing rapidly, transmitting electromagnetic power through the different frequency bands used on the markets, restricting and preventing electronic equipment from all sources of interference has become important. Shields are often used for insulation from a room, equipment, circuit, etc. Electromagnetic radiation sources externally or to avoid harmful internal electromagnetic energy emissions. One of the main issues with the introduction of electrical and electronic technology in the world is electromagnetic interference between devices. Different scientists and industrial enterprises were keenly interested in seeking solutions to this problem. Table sheets are traditionally considered to be the best electromagnetic shielding material, but they are expensive, heavy, flexible, and thermally expanded. However, the use of electronic and electrical equipment of textile items is appropriate because they are lightweight, versatile, and cheaper. Researchers have drawn attention to various solutions, including textile products and composite textiles these textile structures include flexibility and conformity. Face Unwanted electromagnetic emission in combination with the specific EMI source radiation or transmittal to the surrounding electrical system is electrical signals. This noise, coil parts, digital devices and long DC or AC cables can be caused by Electromagnets. At frequencies that can emit energy on radio frequency [1]. Ferromagnetic materials in mix with fibres and textiles end up being electrically conducive and effective in protecting from electromagnetic radiation. For electromagnetic shielding silver, Copper or stainless steel are best combined with staple or filament fibres. For different electromagnetic shielding fabric composite yarns made from mixing metal and textile fibres. It's difficult to weave metallic yarns than the composite yarn. Conducting polymer composites can create better functionality. Moreover, metallic coating over nonwoven fabrics is cost-efficient for commercial use. This paper describes the study on developing metal coating over nonwoven fabric for electromagnetic shielding purposes

Prediction of hydrologic fluxes over the Marmot basin using small scale distributed hydrologic model

The distributed-Hydrology-Soil-Vegetation model (DHSVM) was applied to the Marmot Creek watershed in western Alberta. The purpose of this research was primarily to assess the applicability of the model as hydrologic prediction tool for a snow dominated forested watershed. Climate data from July 2005 to December 2007 were used as forcing data. The model was calibrated and validated for the Marmot Creek watershed conditions using both streamflow and snow water equivalent (SWE). DHSVM was able to accurately simulate the streamflow and snow water equivalent for the simulated years. Because the accuracy of DHSVM simulations was greatly improved through rigorous calibration, this research demonstrates the need for model calibration to a watershed of interest, prior to hydrologic simulations using different landscape scenarios. -- Next, two scenario were used to measure the effect of digital elevation model (DEM) and land cover change on streamflow and snow water equivalent. A hydrologically modified DEM was generated using ANUDEM software and was used to assess the sensitivity of DEM source on model simulations. Earth Observation for Sustainable Development (EOSD) and United States Geological Survey (USGS) land cover maps were also applied to evaluate the influence of land cover source on streamflow and SWE results. These sensitivity studies show that differences observed through direct comparisons of topographic parameters are reflected in the shape and timing of simulated streamflow and snow water equivalent (SWE) results. Results also show that the USGS DEM produced lower peak flows than the ANUDEM DEM and USGS land cover underestimate SWE when compared to the EOSD land cover. -- Overall, the significance of the study is that it broadens the knowledge of DEM and land cover change effects on hydrological processes in snow dominated mountainous watersheds. It thus provides a framework for assessing the vulnerability of watersheds to altered streamflow and SWE regimes attributable to changes in DEM and land cover that occur over large geographical areas and long time-frames

Production and economics of Gangetic mystus (Mystus cavasius) farming under different feed restriction periods in cages of floodplain ecosystem

High feed cost is a major problem for the promotion of a nutrient rich fish like Gangetic mystus (Mystus cavasius) in cages under floodplain ecosystem. To address this problem, production and economics of cage farming of Gangetic mystus were evaluated under different feed restriction periods in Atrai River of Chalan Beel. Four feed restriction periods were tested in floating cages under four different treatments (T1-0 day i.e., regular feeding, T2-1 day, T3-2 days, and T4-3 days feed restriction per week). Fish were fed twice daily with commercial floating pellet containing 32% protein. Water quality parameters (water temperature, dissolved oxygen, pH and ammonia-nitrogen) were within the suitable range for fish culture. Final weight, weight gain, % weight gain, average daily gain, specific growth rate and survival rate were found significantly higher at treatment T1 whereas a better feed conversion ratio was observed in T2. Significantly higher fish production and benefit were also obtained from treatment T2. The present study concluded that Gangetic mystus with a stocking density of 50 fish m–3 fed with 32% protein containing feed maintaining 1 day feeding restriction per week are economically feasible for cage culture in running water

Understanding Dhaka City Traffic Intensity and Traffic Expansion Using Gravity Model

Analysis of traffic pattern recognition and traffic congestion expansion in real time are one of the exciting and challenging tasks which help the government to build a robust and sustainable traffic management system specially in a densely populated city like Dhaka. In this paper, we analyze the traffic intensity for small areas which are also known as junction points or corridors. We describe Dhaka city traffic expansion from a congestion point by using gravity model. However, we process real-time traffic data of Dhaka city rather than depend on survey and interview. We exactly show that traffic expansion of Dhaka city exactly follows gravity model. Expansion of traffic from a congestion point spreads out rapidly to its neighbor and impact of congested point decreases as the distance increases from that congested point. This analysis will help the government making a planned urbanized Dhaka city in order to reduce traffic jam.Comment: 6 pages, 10 citation