Search results for: Tracked Vehicles

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Melissa Hachem, Maxime Loizeau, Nadine Saleh, Isabelle Momas, Lynda Bensefa-Colas

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Professional drivers are exposed inside their vehicles to high levels of air pollutants due to the considerable time they spend close to motor vehicle emissions. Little is known about ultrafine particles (UFP) or black carbon (BC) adverse respiratory health effects compared to the regulated pollutants. We aimed to study the short-term associations between UFP and BC concentrations inside vehicles and (1) the onset of mucosal irritation and (2) the acute changes in lung function of Parisian taxi drivers during a working day. An epidemiological study was carried out on 50 taxi drivers in Paris. UFP and BC were measured inside their vehicles with DiSCmini® and microAeth®, respectively. On the same day, the frequency and the severity of nose, eye, and throat irritations were self-reported by each participant and a spirometry test was performed before and after the work shift. Multivariate analysis was used to evaluate the associations between in-taxis UFP and BC concentrations and mucosal irritation and lung function, after adjustment for potential confounders. In-taxis UFP concentrations ranged from 17.9 to 37.9 × 103 particles/cm³ and BC concentrations from 2.2 to 3.9 μg/m³, during a mean of 9 ± 2 working hours. Significant dose-response relationships were observed between in-taxis UFP concentrations and both nasal irritation and lung function. The increase of in-taxis UFP (for an interquartile range of 20 × 103 particles/cm3) was associated to an increase in nasal irritation (adjusted OR = 6.27 [95% CI: 1.02 to 38.62]) and to a reduction in forced expiratory flow at 25–75% by −7.44% [95% CI: −12.63 to −2.24], forced expiratory volume in one second by −4.46% [95% CI: −6.99 to −1.93] and forced vital capacity by −3.31% [95% CI: −5.82 to −0.80]. Such associations were not found with BC. Incident throat and eye irritations were not related to in-vehicle particles exposure; however, they were associated with outdoor air quality (estimated by the Atmo index) and in-vehicle humidity, respectively. This study is the first to show a significant association, within a short-period of time, between in-vehicle UFP exposure and acute respiratory effects in professional drivers.

Keywords: black carbon, lung function, mucosal irritation, taxi drivers, ultrafine particles

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Authors: Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth, Karl Sammut

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In recent years, large unmanned underwater vehicles such as the Boeing Voyager and Anduril Ghost Shark have been developed. These vessels can be structured to contain onboard internal payload bays. These payload bays can serve a variety of purposes – including the launch and recovery (LAR) of smaller underwater vehicles. The LAR of smaller vessels is extremely important, as it enables transportation over greater distances, increased time on station, data transmission and operational safety. The larger vessel and its payload bay structure complicate the LAR of UUVs in contrast to static docks that are affixed to the seafloor, as they actively impact the local flow field. These flow field impacts require analysis to determine if UUV vessels can be safely launched and recovered inside the motherships. This research seeks to determine the hydrodynamic forces exerted on a vertically over-actuated, small, unmanned underwater vehicle (OUUV) during an internal LAR manoeuvre and compare this to an under-actuated vessel (UUUV). In this manoeuvre, the OUUV is navigated through the stern wake region of the larger vessel to a set point within the internal payload bay. The manoeuvre is simulated using ANSYS Fluent computational fluid dynamics models, covering the entire recovery of the OUUV and UUUV. The analysis of the OUUV is compared against the UUUV to determine the differences in the exerted forces. Of particular interest are the drag, pressure, turbulence and flow field effects exerted as the OUUV is driven inside the payload bay of the larger vessel. The hydrodynamic forces and flow field disturbances are used to determine the feasibility of making such an approach. From the simulations, it was determined that there was no significant detrimental physical forces, particularly with regard to turbulence. The flow field effects exerted by the OUUV are significant. The vertical thrusters exert significant wake structures, but their orientation ensures the wake effects are exerted below the UUV, minimising the impact. It was also seen that OUUV experiences higher drag forces compared to the UUUV, which will correlate to an increased energy expenditure. This investigation found no key indicators that recovery via a mothership payload bay was not feasible. The turbulence, drag and pressure phenomenon were of a similar magnitude to existing static and towed dock structures.

Keywords: underwater vehicles, submarine, autonomous underwater vehicles, AUV, computational fluid dynamics, flow fields, pressure, turbulence, drag

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Authors: Nur Syahidatul Idany Abdul Ghani, Rahizar Ramli, Jamilah Mohamad, Ahmad Saifizul, Mohamed Rehan Karim

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Increasing fatalities in road accidents in Malaysia over the last 10 years are quite alarming. Based on Malaysian Institute of Road Safety Research (Miros) latest research ‘Predicting Malaysian Road Fatalities for year 2020; it is predicted that road fatalities in Malaysia for 2015 is 8,780 and 10,716 for the year 2020 which 30 percent of fatalities were caused by accidents involving commercial vehicles. Government, related agencies and NGOs have continuously and persistently work to reduce the statistics through enforcement, educating the public, training to drivers, road safety campaigns, advertisements etc. However, the trend of casualties does not show encouraging pattern but instead, steadily growing. Thus, this comparative study reviews the literature pertaining on method of measurement used to evaluate commercial drivers competency. In several studies driving competency has been assessed with different assessment based on the license procedures and requirements according to the country regulation. The assessment criteria that has been establish for commercial drivers generally focus on driving tasks and assessment e.g. theory test, medical test and road assessment rather than driving competency test or physical test. Realizing the importance of specific assessment test for drivers competency this comparative study reviews the most discussed literature related to competency assessment method to identify competency of the drivers include (1. judgement and reaction, 2. skill of drivers, 3. experiences and fatigue). The concluding analysis of this paper is a comparative table for assessment methodology to access driver’s competency. A comparative study is a further discussion reviewing past literature to provide an overview on existing assessment test and potential subject matters that can be identified for further studies to increase awareness of the drivers, passengers as well as the authorities about the importance of competent drivers in order to improve safety in commercial vehicles.

Keywords: commercial vehicles, driver’s competency, specific assessment

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Authors: Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth, Karl Sammut

Abstract:

- In recent years, large unmanned underwater vehicles such as the Boeing Voyager and Anduril Ghost Shark have been developed. These vessels can be structured to contain onboard internal payload bays. These payload bays can serve a variety of purposes – including the launch and recovery (LAR) of smaller underwater vehicles. The LAR of smaller vessels is extremely important, as it enables transportation over greater distances, increased time on station, data transmission and operational safety. The larger vessel and its payload bay structure complicate the LAR of UUVs in contrast to static docks that are affixed to the seafloor, as they actively impact the local flow field. These flow field impacts require analysis to determine if UUV vessels can be safely launched and recovered inside the motherships. This research seeks to determine the hydrodynamic forces exerted on a vertically over-actuated, small, unmanned underwater vehicle (OUUV) during an internal LAR manoeuvre and compare this to an under-actuated vessel (UUUV). In this manoeuvre, the OUUV is navigated through the stern wake region of the larger vessel to a set point within the internal payload bay. The manoeuvre is simulated using ANSYS Fluent computational fluid dynamics models, covering the entire recovery of the OUUV and UUUV. The analysis of the OUUV is compared against the UUUV to determine the differences in the exerted forces. Of particular interest are the drag, pressure, turbulence and flow field effects exerted as the OUUV is driven inside the payload bay of the larger vessel. The hydrodynamic forces and flow field disturbances are used to determine the feasibility of making such an approach. From the simulations, it was determined that there was no significant detrimental physical forces, particularly with regard to turbulence. The flow field effects exerted by the OUUV are significant. The vertical thrusters exert significant wake structures, but their orientation ensures the wake effects are exerted below the UUV, minimising the impact. It was also seen that OUUV experiences higher drag forces compared to the UUUV, which will correlate to an increased energy expenditure. This investigation found no key indicators that recovery via a mothership payload bay was not feasible. The turbulence, drag and pressure phenomenon were of a similar magnitude to existing static and towed dock structures.

Keywords: underwater vehicles, submarine, autonomous underwater vehicles, auv, computational fluid dynamics, flow fields, pressure, turbulence, drag

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Authors: Kushal Kumar Chode

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Increase in demand for fuel saving and demand for faster vehicles with decent fuel economy, researchers around the world started investigating in various passive flow control devices to improve the fuel efficiency of vehicles. In this paper, A roof fairing was investigated for reducing the aerodynamic drag of a bluff body. The bluff body considered for this work is Ahmed model with a rake angle of 25deg was and subjected to flow with a velocity of 40m/s having Reynolds number of 2.68million was analysed using a commercial Computational Fluid Dynamic (CFD) code Star CCM+. It was evident that pressure drag is the main source of drag on an Ahmed body from the initial study. Adding a roof fairing has delayed the flow separation and resulted in delaying wake formation, thus improving the pressure in near weak and reducing the wake region. Adding a roof fairing of height and length equal to 1/7H and 1/3L respectively has shown a drag reduction by 9%. However, an optimised fairing, which was obtained by changing height, length and width by 5% increase, recorded a drag reduction close 12%.

Keywords: Ahmed model, aerodynamic drag, passive flow control, roof fairing, wake formation

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Authors: Mortez Alijani, Anas Osman

Abstract:

Recently, the popularity of Unmanned aerial vehicles (UAVs) has skyrocketed amidst the unprecedented events and the global pandemic, as they play a key role in both the security and health sectors, through surveillance, taking test samples, transportation of crucial goods and spreading awareness among civilians. However, the process of designing and producing such aerial robots is suppressed by the internal and external constraints that pose serious challenges. Landing is one of the key operations during flight, especially, the autonomous landing of UAVs on a moving platform is a scientifically complex engineering problem. Typically having a successful automatic landing of UAV on a moving platform requires accurate localization of landing, fast trajectory planning, and robust control planning. To achieve these goals, the information about the autonomous landing process such as the intersection point, the position of platform/UAV and inclination angle are more necessary. In this study, the mathematical approach to this problem in the X-Y axis based on the inclination angle and position of UAV in the landing process have been presented. The experimental results depict the accurate position of the UAV, intersection between UAV and moving platform and inclination angle in the landing process, allowing prediction of the intersection point.

Keywords: autonomous landing, inclination angle, unmanned aerial vehicles, moving platform, X-Y axis, intersection point

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Authors: Ahmed Kiani

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The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Ioan Corneliu Salisteanu, Valentin Dogaru Ulieru, Mihaita Nicolae Ardeleanu, Alin Pohoata, Bogdan Salisteanu, Stefan Broscareanu

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Creating a personalized statistic for an individual within the population using IT systems, based on the searches and intercepted spheres of interest they manifest, is just one 'atom' of the artificial intelligence analysis network. However, having the ability to generate statistics based on individual data intercepted from large demographic areas leads to reasoning like that issued by a human mind with global strategic ambitions. The DiaMOTO device is a technical sensory system that allows the interception of car events caused by a driver, positioning them in time and space. The device's connection to the vehicle allows the creation of a source of data whose analysis can create psychological, behavioural profiles of the drivers involved. The SiaMOTO system collects data from many vehicles equipped with DiaMOTO, driven by many different drivers with a unique fingerprint in their approach to driving. In this paper, we aimed to explain the software infrastructure of the SiaMOTO system, a system designed to monitor and improve driver driving behaviour, as well as the criteria and algorithms underlying the intelligent analysis process.

Keywords: artificial intelligence, data processing, driver behaviour, driver monitoring, SiaMOTO

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Nikhat Iqbal Tamboli

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INTRODUCTION: road traffic accidents (RTAs) are one of the leading and common causes of ocular injuries especially in developing countries like India which are preventable with certain measures and so it is of public health importance. AIM: To study incidence and clinical presentation of ocular morbidity in road traffic accidents. METHOD: Prospective cross-sectional study was conducted on 360 patients reported in department of ophthalmology. Detailed ocular examination and relevant investigations done. RESULTS: Incidence of ocular injuries is 23%. male:female ratio is 4.5:1.Cases having Sub conjunctival haemorrhage [74].eccymosis[217]. lid lcerations [164]orbital fracture[12] corneal tear [7]corneal abrasion[2] sclera tear[6] hyphaema[4] traumatic mydriasis [7]traumatic cataract [2]vitreous haemorrhage [1]traumatic optic neuropathy[1].Maximum cases in age group 20-40 years, with two wheeler vehicles 94.7% .Under influence of alcohol 13.3%. CONCLUSION: Younger age group with male preponderance is involved in ocular trauma due to road traffic accidents .maximum cases reported are with anterior segment injuries. Alcohol and two wheeler vehicles are common risk factors. Injuries involving cornea had bad prognosis and involving retina had worst prognosis.

Keywords: ocular morbidity, eye trauma, RTA, eye injury

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

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Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

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Power systems are innately uncertain systems. To face with such uncertain systems, robust uncertainty assessment tools are appealed. This paper inspects the uncertainty assessment formulation of the load flow (LF) problem considering different kinds of uncertainties, developed in its companion paper through some case studies. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. The load and wind power generation are considered as probabilistic uncertain variables and the electric vehicles (EVs) and gas turbine distributed generation (DG) units are considered as possibilistic uncertain variables. The cumulative distribution function (CDF) of the system output parameters obtained by the pure probabilistic method lies within the belief and plausibility functions obtained by the joint propagation approach. Furthermore, the imprecision in the DG parameters is explicitly reflected by the gap between the belief and plausibility functions. This gap, due to the epistemic uncertainty on the DG resources parameters grows as the penetration level increases.

Keywords: electric vehicles, joint possibilistic- probabilistic uncertainty modeling, uncertain load flow, wind turbine generator

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Authors: Francesca Fermi, Paola Astegiano, Angelo Martino, Stephanie Heitel, Michael Krail

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In order to achieve the targeted emission reductions for the decarbonisation of the European economy by 2050, fundamental contributions are required from both energy and transport sectors. The objective of this paper is to analyse the impacts of a largescale diffusion of e-vehicles, either battery-based or fuel cells, together with the implementation of transport policies aiming at decreasing the use of motorised private modes in order to achieve greenhouse gas emission reduction goals, in the context of a future high share of renewable energy. The analysis of the impacts and challenges of future scenarios on transport sector is performed with the ASTRA (ASsessment of TRAnsport Strategies) model. ASTRA is a strategic system-dynamic model at European scale (EU28 countries, Switzerland and Norway), consisting of different sub-modules related to specific aspects: the transport system (e.g. passenger trips, tonnes moved), the vehicle fleet (composition and evolution of technologies), the demographic system, the economic system, the environmental system (energy consumption, emissions). A key feature of ASTRA is that the modules are linked together: changes in one system are transmitted to other systems and can feed-back to the original source of variation. Thanks to its multidimensional structure, ASTRA is capable to simulate a wide range of impacts stemming from the application of transport policy measures: the model addresses direct impacts as well as second-level and third-level impacts. The simulation of the different scenarios is performed within the REFLEX project, where the ASTRA model is employed in combination with several energy models in a comprehensive Modelling System. From the transport sector perspective, some of the impacts are driven by the trend of electricity price estimated from the energy modelling system. Nevertheless, the major drivers to a low carbon transport sector are policies related to increased fuel efficiency of conventional drivetrain technologies, improvement of demand management (e.g. increase of public transport and car sharing services/usage) and diffusion of environmentally friendly vehicles (e.g. electric vehicles). The final modelling results of the REFLEX project will be available from October 2018. The analysis of the impacts and challenges of future scenarios is performed in terms of transport, environmental and social indicators. The diffusion of e-vehicles produces a consistent reduction of future greenhouse gas emissions, although the decarbonisation target can be achieved only with the contribution of complementary transport policies on demand management and supporting the deployment of low-emission alternative energy for non-road transport modes. The paper explores the implications through time of transport policy measures on mobility and environment, underlying to what extent they can contribute to a decarbonisation of the transport sector. Acknowledgements: The results refer to the REFLEX project which has received grants from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 691685.

Keywords: decarbonisation, greenhouse gas emissions, e-mobility, transport policies, energy

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Authors: Anusha De, Bjorn Van Campenhout

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Faced with imperfect information, economic actors use judgment and perceptions in decision-making. Inaccurate perceptions or false beliefs may result in inefficient value chains, and systematic bias in perceptions may affect inclusiveness. In this paper, perceptions in Ugandan maize supply chains are studied. A random sample of maize farmers where they were asked to rate other value chain actors—agro-input dealers, assembly traders and maize millers—on a set of important attributes such as service quality, price competitiveness, ease of access, and overall reputation. These other value chain actors are tracked and asked to assess themselves on the same attributes. It is observed that input dealers, traders and millers assess themselves more favorably than farmers do. Zooming in on heterogeneity in perceptions related to gender, it is evident that women rate higher than men. The sex of the actor being rated does not affect the rating.

Keywords: gender, input dealers, maize supply chain, perceptions, processors

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Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

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With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

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Authors: Suraj Gururaj, Sumantha Udupa U.

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Browsing the Web has emerged as the de facto activity performed on the Internet. Although browsing gets tracked, the manageability aspect of Web browsing history is very poor. In this paper, we have a workable solution implemented by using machine learning and natural language processing techniques for efficient manageability of user’s browsing history. The significance of adding such a capability to a Web browser is that it ensures efficient and quick information retrieval from browsing history, which currently is very challenging. Our solution guarantees that any important websites visited in the past can be easily accessible because of the intelligent and automatic classification. In a nutshell, our solution-based paper provides an implementation as a browser extension by intelligently classifying the browsing history into most relevant category automatically without any user’s intervention. This guarantees no information is lost and increases productivity by saving time spent revisiting websites that were of much importance.

Keywords: adhoc retrieval, Chrome extension, supervised learning, tile, Web personalization

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Authors: Muhammad Dawood Idrees, Maria Hafeez, Arsalan Ansari

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Toll tax collection is the earliest method of tax collection and revenue generation. This revenue is utilized for the development of roads networks, maintenance, and connecting to roads and highways across the country. Pakistan is one of the biggest countries, covers a wide area of land, roads networks, and motorways are important source of connecting cities. Every day millions of people use motorways, and they have to stop at toll plazas to pay toll tax as majority of toll plazas are manually collecting toll tax. The purpose of this study is to calculate the waiting time of vehicles at Karachi Hyderabad (M-9) motorway. As Karachi is the biggest city of Pakistan and hundreds of thousands of people use this route to approach other cities. Currently, toll tax collection is manual system which is a major cause for long time waiting at toll plaza. This study calculates the waiting time of vehicles, fuel consumed in waiting time, manpower employed at toll plaza as all process is manual, and it also leads to mental and physical fatigue of driver. All wastages of sources are also calculated, and a most feasible automatic toll tax collection system is proposed which is not only beneficial to reduce waiting time but also beneficial in reduction of fuel, reduction of manpower employed, and reduction in physical and mental fatigue. A cost comparison in terms of wastages is also shown between manual and automatic toll tax collection system (E-Z Pass). Results of this study reveal that, if automatic tool collection system is implemented at Karachi to Hyderabad motorway (M-9), there will be a significance reduction in waiting time of vehicles, which leads to reduction of fuel consumption, environmental pollution, mental and physical fatigue of driver. All these reductions are also calculated in terms of money (Pakistani rupees) and it is obtained that millions of rupees can be saved by using automatic tool collection system which will lead to improve the economy of country.

Keywords: toll tax collection, waiting time, wastages, driver fatigue

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Aymen Laadhari, Gábor Székely

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This paper is concerned with the development of a fully implicit and purely Eulerian fluid-structure interaction method tailored for the modeling of the large deformations of elastic membranes in a surrounding Newtonian fluid. We consider a simplified model for the mechanical properties of the membrane, in which the surface strain energy depends on the membrane stretching. The fully Eulerian description is based on the advection of a modified surface tension tensor, and the deformations of the membrane are tracked using a level set strategy. The resulting nonlinear problem is solved by a Newton-Raphson method, featuring a quadratic convergence behavior. A monolithic solver is implemented, and we report several numerical experiments aimed at model validation and illustrating the accuracy of the presented method. We show that stability is maintained for significantly larger time steps.

Keywords: finite element method, implicit, level set, membrane, Newton method

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Authors: Chun-Liang Wu, Kai-Ping Shaw, Cheng-Ping Yu, Wu-Chien Chien, Hsiao-Ting Chen, Shao-Huang Wu

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Objective: This study analyzed three criminal judicial cases. We applied the damage analysis of the two vehicles to verify other evidence, such as dashboard camera records of each accident, reconstruct the scenes, and pursue the truth. Methods: Evidence analysis, the method is to collect evidence and the reason for the results in judicial procedures, then analyze the involved damage evidence to verify other evidence. The collision damage analysis method is to inspect the damage to the vehicles and utilize the principles of tool mark analysis, Newtonian physics, and vehicle structure to understand the relevant factors when the vehicles collide. Results: Case 1: Sedan A turned right at the T junction and collided with Scooter B, which was going straight on the left road. The dashboard camera records showed that the left side of Sedan A’s front bumper collided with the body of Scooter B and rider B. After the analysis of the study, the truth was that the front of the left side of Sedan A impacted the right pedal of Scooter B and the right lower limb of rider B. Case 2: Sedan C collided with Scooter D on the left road at the crossroads. The dashboard camera record showed that the left side of the Sedan C’s front bumper collided with the body of Scooter D and rider D. After the analysis of the study, the truth was that the left side of the Sedan C impacted the left side of the car body and the front wheel of Scooter D and rider D. Case 3: Sedan E collided with Scooter F on the right road at the crossroads. The dashboard camera record showed that the right side of the Sedan E’s front bumper collided with the body of Scooter F and rider F. After the analysis of the study, the truth was that the right side of the front bumper and the right side of the Sedan F impacted the Scooter. Conclusion: The application of collision damage analysis in the reconstruction of a sedan-scooter collision could discover the truth and provide the basis for judicial justice. The cases and methods could be the reference for the road safety policy.

Keywords: evidence analysis, collision damage analysis, accident reconstruction, sedan-scooter collision, dashboard camera records

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Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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Authors: Aritra Das, Tanmay Mahapatra, Prabir Maharana, Sridhar Srikantiah

Abstract:

In the absence of adequate well-equipped neonatal-care facilities serving rural Bihar, India, the practice of essential home-based newborn-care remains critically important for reduction of neonatal and infant mortality, especially among pre-term and small-for-gestational-age (Low-birth-weight) newborns. To improve the child health parameters in Bihar, ‘Very-Low-Birth-Weight (vLBW) Tracking’ intervention is being conducted by CARE India, since 2015, targeting public facility-delivered newborns weighing ≤2000g at birth, to improve their identification and provision of immediate post-natal care. To assess the effectiveness of the intervention, 200 public health facilities were randomly selected from all functional public-sector delivery points in Bihar and various outcomes were tracked among the neonates born there. Thus far, one pre-intervention (Feb-Apr’2015-born neonates) and three post-intervention (for Sep-Oct’2015, Sep-Oct’2016 and Sep-Oct’2017-born children) follow-up studies were conducted. In each round, interviews were conducted with the mothers/caregivers of successfully-tracked children to understand outcome, service-coverage and care-seeking during the neonatal period. Data from 171 matched facilities common across all rounds were analyzed using SAS-9.4. Identification of neonates with birth-weight ≤ 2000g improved from 2% at baseline to 3.3%-4% during post-intervention. All indicators pertaining to post-natal home-visits by frontline-workers (FLWs) improved. Significant improvements between baseline and post-intervention rounds were also noted regarding mothers being informed about ‘weak’ child – at the facility (R1 = 25 to R4 = 50%) and at home by FLW (R1 = 19%, to R4 = 30%). Practice of ‘Kangaroo-Mother-Care (KMC)’– an important component of essential newborn care – showed significant improvement in postintervention period compared to baseline in both facility (R1 = 15% to R4 = 31%) and home (R1 = 10% to R4=29%). Increasing trend was noted regarding detection and birth weight-recording of the extremely low-birth-weight newborns (< 1500 g) showed an increasing trend. Moreover, there was a downward trend in mortality across rounds, in each birth-weight strata (< 1500g, 1500-1799g and >= 1800g). After adjustment for the differential distribution of birth-weights, mortality was found to decline significantly from R1 (22.11%) to R4 (11.87%). Significantly declining trend was also observed for both early and late neonatal mortality and morbidities. Multiple regression analysis identified - birth during immediate post-intervention phase as well as that during the maintenance phase, birth weight > 1500g, children of low-parity mothers, receiving visit from FLW in the first week and/or receiving advice on extra care from FLW as predictors of survival during neonatal period among vLBW newborns. vLBW tracking was found to be a successful and sustainable intervention and has already been handed over to the Government.

Keywords: weak newborn tracking, very low birth weight babies, newborn care, community response

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Authors: Kikuo Asai, Yuji Sugimoto

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We developed a prototype system for multiplayer RC-car driving in a collaborative Augmented Reality (AR) environment. The tele-existence environment is constructed by superimposing digital data onto images captured by a camera on an RC-car, enabling players to experience an augmented coexistence of the digital content and the real world. Marker-based tracking was used for estimating position and orientation of the camera. The plural RC-cars can be operated in a field where square markers are arranged. The video images captured by the camera are transmitted to a PC for visual tracking. The RC-cars are also tracked by using an infrared camera attached to the ceiling, so that the instability is reduced in the visual tracking. Multimedia data such as texts and graphics are visualized to be overlaid onto the video images in the geometrically correct manner. The prototype system allows a tele-existence sensation to be augmented in a collaborative AR environment.

Keywords: multiplayer, RC-car, collaborative environment, augmented reality

Procedia PDF Downloads 259

Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control

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Authors: Marie Bieber, Fabrice Cosson, Olivier Schmitt

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Europe's Global Navigation Satellite System, Galileo, provides worldwide positioning and navigation services. The satellites in space are only one part of the Galileo system. An extensive ground infrastructure is essential to oversee the satellites and ensure accurate navigation signals. High reliability and availability of the entire Galileo system are crucial to continuously provide positioning information of high quality to users. Outages are tracked, and operational availability is regularly assessed. A highly flexible and adaptive tool has been developed to automate the Galileo system availability analysis. Not only does it enable a quick availability consolidation, but it also provides first steps towards improving the data quality of maintenance tickets used for the analysis. This includes data import and data preparation, with a focus on processing strings used for classification and identifying faulty data. Furthermore, the tool allows to handle a low amount of data, which is a major constraint when the aim is to provide accurate statistics.

Keywords: availability, data quality, system performance, Galileo, aerospace

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Authors: Shaherah Jordan, Paula Vandergert

Abstract:

The discussion on public charging infrastructure is usually framed around the ‘chicken-egg’ challenge of consumers feeling reluctant to purchase without the necessary infrastructure and policymakers reluctant to invest in the infrastructure without the demand. However, public charging infrastructure may be more crucial to electric vehicle (EV) adoption than previously thought. Historically, access to residential charging was thought to be a major factor in potential for growth in the EV market as it offered a guaranteed place for a vehicle to be charged. The purpose of this study is to understand how the built environment may encourage uptake of EVs by seeking a correlation between EV ownership and public charging points in an urban and densely populated city such as London. Using a statistical approach with data from the Department for Transport and Zap-Map, a statistically significant correlation was found between the total (slow, fast and rapid) number of public charging points and a number of EV registrations per borough – with the strongest correlation found between EV registrations and rapid chargers. This research does not explicitly prove that there is a cause and effect relationship between public charging points EVs but challenges some of the previous literature which indicates that public charging infrastructure is not as important as home charging. Furthermore, the study provides strong evidence that public charging points play a functional and psychological role in the adoption of EVs and supports the notion that the built environment can influence human behaviour.

Keywords: behaviour change, electric vehicles, public charging infrastructure, transportation

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Authors: Ali Babaei

Abstract:

There is a worldwide growing tendency toward construction of infrastructures with the possibility of private sector participation instead of free exploitation of public infrastructures. The construction and development of roads through private sector participation is performed by different countries because of appropriate results and benefits such as compensation of public budget deficit in road construction and maintenance and responding to traffic growth (demand). Toll is the most definite form of budget provision in road development. There are two issues in the toll rate assignment: A. costing of transport, B. Cost allocation and distribution of cost between different types of vehicles as each vehicle pay its own share. There can be different goals in toll collection and its extent is variable according to the strategy of toll collection. Costing principles in different countries are based on inclusion of the whole transport and not peculiar to the toll roads. For example, fuel tax policy functions where the road network users pay transportation cost (not just users of toll road). Whereas transportation infrastructures in Iran are free, these methods are not applicable. In Iran, different toll freeways have built by public investment and government provides participation in the road construction through encouragement of financial institutions. In this paper, the existing policies about the toll roads are studied and then the appropriate method of costing and cost allocation to different vehicles is introduced.

Keywords: toll allocation, road pricing, transportation, financial and industrial systems

Procedia PDF Downloads 334