Search results for: automated vehicles

Authors: Gregory E. Ofili

Abstract:

Introduction and Objective: Climate change and a global economy mean farmers must adapt and gain access to affordable and reliable automation technologies. Key barriers include a lack of transportation, electricity, and internet service, coupled with costly enabling technologies and limited local subject matter expertise. Methodology/Approach: Resourcefulness is essential to mechanization on a farm. This runs contrary to the tech industry practice of planned obsolescence and disposal. One solution is plug-and-play hardware that allows farmer to assemble, repair, program, and service their own fleet of industrial machines. To that end, we developed a method of manufacturing low-cost utility robots, transport vehicles, and solar/wind energy harvesting systems, all running on an open-source Robot Operating System (ROS). We demonstrate this technology by fabricating a utility robot and an all-terrain (4X4) utility vehicle. Constructed of aluminum trusses and weighing just 40 pounds, yet capable of transporting 200 pounds of cargo, on sale for less than $2,000. Conclusions & Policy Implications: Electricity, internet, and automation are essential for productivity and competitiveness. With planned obsolescence, the priorities of technology suppliers are not aligned with the farmer’s realities. This patent-pending method of manufacturing low-cost industrial robots and electric vehicles has met its objective. To create low-cost machines, the farmer can assemble, program, and repair with basic hand tools.

Keywords: automation, robotics, utility robot, small-hold farm, robot operating system

Procedia PDF Downloads 70

Authors: Imam Taufiqurrahman, Anugrah Adiwilaga, Egi Hidayat, Bambang Riyanto Trilaksono

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Autonomous Underwater Vehicle glider is one of the renewal of underwater vehicles. This vehicle is one of the autonomous underwater vehicles that are being developed in Indonesia. Glide ability is obtained by controlling the buoyancy and attitude of the vehicle using the movers within the vehicle. The glider motion mechanism is expected to provide energy resistance from autonomous underwater vehicles so as to increase the cruising range of rides while performing missions. The control system on the vehicle consists of three parts: controlling the attitude of the pitch, the buoyancy engine controller and the yaw controller. The buoyancy and pitch controls on the vehicle are sequentially referring to the finite state machine with pitch angle and depth of diving inputs to obtain a gliding cycle. While the yaw control is done through the rudder for the needs of the guide system. This research is focused on design and implementation of control system of Autonomous Underwater Vehicle glider based on PID anti-windup. The control system is implemented on an ARM TS-7250-V2 device along with a mathematical model of the vehicle in MATLAB using the hardware-in-the-loop simulation (HILS) method. The TS-7250-V2 is chosen because it complies industry standards, has high computing capability, minimal power consumption. The results show that the control system in HILS process can form glide cycle with depth and angle of operation as desired. In the implementation using half control and full control mode, from the experiment can be concluded in full control mode more precision when tracking the reference. While half control mode is considered more efficient in carrying out the mission.

Keywords: control system, PID, underwater glider, marine robotics

Procedia PDF Downloads 374

Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu

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Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.

Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior

Procedia PDF Downloads 104

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

Procedia PDF Downloads 129

Authors: Huey-Kuo Chen

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This paper applies directional marginal productivity model to study the shadow price of emissions by transportation modes in the years of 2011 and 2013 with the aim to provide a reference for policy makers to improve the emission of pollutants. One input variable (i.e., energy consumption), one desirable output variable (i.e., vehicle kilometers traveled) and three undesirable output variables (i.e., carbon dioxide, sulfur oxides and nitrogen oxides) generated by road transportation modes were used to evaluate directional marginal productivity and directional shadow price for 18 transportation modes. The results show that the directional shadow price (DSP) of SOx is much higher than CO2 and NOx. Nevertheless, the emission of CO2 is the largest among the three kinds of pollutants. To improve the air quality, the government should pay more attention to the emission of CO2 and apply the alternative solution such as promoting public transportation and subsidizing electric vehicles to reduce the use of private vehicles.

Keywords: marginal productivity, road transportation modes, shadow price, undesirable outputs

Procedia PDF Downloads 147

Authors: Flóra Pomázi, Sándor Baranya, Zoltán Szalai

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A harmonized monitoring of the suspended sediment transport along such a large river as the world’s most international river, the Danube River, is a rather challenging task. The traditional monitoring method in Hungary is obsolete but using indirect measurement devices and techniques like optical backscatter sensors (OBS), laser diffraction or acoustic backscatter sensors (ABS) could provide a fast and efficient alternative option of direct methods. However, these methods are strongly sensitive to the particle characteristics (i.e. particle shape, particle size and mineral composition). The current method does not provide sufficient information about particle size distribution, mineral analysis is rarely done, and the shape of the suspended sediment particles have not been examined yet. The aims of the study are (1) to determine the particle characterisation of suspended sediment in the Danube River using advanced particle characterisation methods as laser diffraction and automated imaging, and (2) to perform a sensitivity analysis of the indirect methods in order to determine the impact of suspended particle characteristics. The particle size distribution is determined by laser diffraction. The particle shape and mineral composition analysis is done by the Morphologi G3ID image analyser. The investigated indirect measurement devices are the LISST-Portable|XR, the LISST-ABS (Sequoia Inc.) and the Rio Grande 1200 kHz ADCP (Teledyne Marine). The major findings of this study are (1) the statistical shape of the suspended sediment particle - this is the first research in this context, (2) the actualised particle size distribution – that can be compared to historical information, so that the morphological changes can be tracked, (3) the actual mineral composition of the suspended sediment in the Danube River, and (4) the reliability of the tested indirect methods has been increased – based on the results of the sensitivity analysis and the previous findings.

Keywords: advanced particle characterisation, automated imaging, indirect methods, laser diffraction, mineral composition, suspended sediment

Procedia PDF Downloads 146

Authors: Getachew Demeissie Ayalew, Yongtao Sun, Yang Yang

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The spiral welded pipe manufacturing industry requires strict production standards for automated grinders for welding seams. However, traditional grinding machines in this sector are insufficient due to a lack of quality control protocols and inconsistent performance. This research aims to improve the quality of spiral welded pipes by developing intelligent automated abrasive belt grinding equipment. The system has equipped with six degrees of freedom (6 DOF) KUKA KR360 industrial robots, enabling concurrent grinding operations on both internal and external welds. The grinding robot control system is designed with a PLC, and a human-machine interface (HMI) system is employed for operations. The system includes an electric speed controller, data connection card, DC driver, analog amplifier, and HMI for input data. This control system enables the grinding of spiral welded pipe. It ensures consistent production quality and cost-effectiveness by reducing the product life cycle and minimizing risks in the working environment.

Keywords: Intelligent Systems, Spiral Welded Pipe, Grinding, Industrial Robot, End-Effector, PLC Controller System, 3D Laser Sensor, HMI.

Procedia PDF Downloads 296

Authors: Wei Kunkun, Cao Wanyang, Xu Yujie, Qiao Yuzhi, Liu Yingning

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The reasonable design of bus parking spaces can improve the traffic capacity of the station and reduce traffic congestion. In order to reasonably determine the number of berths at BRT (Bus Rapid Transit) stops, it is based on the actual bus rapid transit station observation data, scheduling data, and passenger flow data. Optimize the number of station berths from the perspective of optimizing the balance of supply and demand at the site. Combined with the classical capacity calculation model, this paper first analyzes the important factors affecting the traffic capacity of BRT stops by using SPSS PRO and MATLAB programming software, namely the distribution of BRT stops and the distribution of BRT stop time. Secondly, the method of calculating the number of the classic human capital management (HCM) model is optimized based on the actual passenger demand of the station, and the method applicable to the actual number of station berths is proposed. Taking Gangding Station of Zhongshan Avenue Bus Rapid Transit Corridor in Guangzhou as an example, based on the calculation method proposed in this paper, the number of berths of sub-station 1, sub-station 2 and sub-station 3 is 2, which reduces the road space of the station by 33.3% compared with the previous berth 3 of each sub-station, and returns to social vehicles. Therefore, under the condition of ensuring the passenger flow demand of BRT stations, the road space of the station is reduced, and the road is returned to social vehicles, the traffic capacity of social vehicles is improved, and the traffic capacity and efficiency of the BRT corridor system are improved as a whole.

Keywords: urban transportation, bus rapid transit station, HCM model, capacity, number of berths

Procedia PDF Downloads 95

Authors: Pakhil Singh, Rahul Singh, Mohammad Saad Alam, Yasser Rafat

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The battery management system is an essential package/system which ensures optimum performance and safety of a battery by monitoring the key essential parameters of the battery like the voltage, current, temperature, state of charge, state of health during charging and discharging. This can be accomplished using outputs of various sensors employed to serve the purpose. The increasing demand for electricity generation from renewable energy sources requires proper storage and hence a proper monitoring system as well. A battery management system is required in wide applications ranging from renewable energy storage systems, off-grid solar PV applications to electric vehicles. The aim of this paper is to study the parameters used in monitoring various battery operating conditions and proposes the usage of the internet of things (IoT) to implement a reliable battery management system.

Keywords: electric vehicles, internet of things, sensors, state of charge, state of health

Procedia PDF Downloads 198

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

Procedia PDF Downloads 686

Authors: M. Moharami Gargari, S. Javdani Zamani, A. Mohammadnejad, S. Abuali

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As maritime container transport is developing fast, the need arises for efficient operations at container terminals. One of the most important determinants of container handling efficiency is the productivity of quay cranes and internal transportation vehicles, which are responsible transporting of containers for unloading and loading operations for container vessels. For this reason, this paper presents an integrated mathematical model formulation for discrete berths with quay cranes and internal transportations vehicles. The problems have received increasing attention in the literature and the present paper deals with the integration of these interrelated problems. A new mixed integer linear formulation is developed for the Berth Allocation Problem (BAP), Quay Crane Assignment and Scheduling Problem (QCASP) and Internal Transportation Scheduling (ITS), which accounts for cranes and trucks positioning conditions.

Keywords: discrete berths, container terminal, truck scheduling, dynamic vessel arrival

Procedia PDF Downloads 400

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

Procedia PDF Downloads 259

Authors: Reza Bahboodian

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One of the most important factors in the use of construction machinery is the fuel consumption cost of this equipment. The use of diesel engines in off-road vehicles is an important source of nitrogen oxides and particulate matter. Emissions of nitrogen oxides and particulate matter 10 in off-road vehicles (construction and mining) may be high. Due to the high cost of fuel, it is necessary to minimize fuel consumption. Factors affecting the fuel consumption of these cars are very diverse. Climate changes such as changes in pressure, temperature, humidity, fuel type selection, type of gearbox used in the car are effective in fuel consumption and pollution, and engine efficiency. In this paper, methods for reducing fuel consumption and pollutants by considering valid European and European standards are examined based on new methods such as hybridization, optimal gear change, adding hydrogen to diesel fuel, determining optimal working fluids, and using oxidation catalysts.

Keywords: improve fuel consumption, construction machinery, pollutant reduction, determining the optimal working cycle

Procedia PDF Downloads 161

Authors: Ramalan Musa Yerima

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The paper titled “loading by number” explained a strategy developed recently by Zonal Commanding Officer of the Federal Road Safety Corps of Nigeria, covering Sokoto, Kebbi and Zamfara States of Northern Nigeria. The strategy is aimed at reducing competition, which will invariably leads to the reduction in speed, reduction in dangerous driving, reduction in crash rate, reduction in injuries, reduction in property damages and reduction in death through road traffic crashes (RTC). This research paper presents a study focused on enhancing the safety of commercial vehicles. The background of this study highlights the alarming statistics related to commercial vehicle crashes in Nigeria with focus on Sokoto, Kebbi and Zamfara States, which often result in significant damage to property, loss of lives, and economic costs. The significance and aims is to investigate and propose effective strategy to enhance the safety of commercial vehicles. The study recognizes the pressing need for heightened safety measures in commercial transportation, as it impacts not only the well-being of drivers and passengers but also the overall public safety. To achieve the objectives, an examination of accident data, including causes and contributing factors, was performed to identify critical areas for improvement. The major finding of the study reveals that when competition comes into play within the realm of commercial driving, it has detrimental effects on road safety and resource management. Commercial drivers are pushed to complete their routes quickly, deliver goods on time or they pushed themselves to arrive quickly for more passengers and new contracts. This competitive environment, fuelled by internal and external pressures such as tight deadlines, poverty and greed, often leads to sad endings. The study recommend that if a strategy called loading by number is integrated with other multiple safety measures such as driver training programs, regulatory enforcement, and infrastructure improvements, commercial vehicle safety can be significantly enhanced. "Loading by Number” approach is design to ensure that the sequence of departure of drivers from motor park ‘A’ would be communicated to motor park officials of park ‘B’, which would be considered sequentially when giving them returning passengers, regardless of the first to arrive. In conclusion, this paper underscores the significance of improving the safety measures of commercial vehicles, as they are often larger and heavier than other vehicles on the road. Whenever they are involved in accidents, the consequences can be more severe. Commercial vehicles are also frequently involved in long-haul or interstate transportation, which means they cover longer distances and spend more time on the road. This increased exposure to driving conditions increases the probability of accidents occurring. By implementing the suggested measures, policymakers, transportation authorities, and industry stakeholders can work collectively towards ensuring a safer commercial transportation system.

Keywords: commercial, safety, strategy, transportation

Procedia PDF Downloads 61

Authors: Ramalan Musa Yerima

Abstract:

The paper titled “Loading by number” explained a strategy developed recently by the Zonal Commanding Officer of the Federal Road Safety Corps of Nigeria, covering Sokoto, Kebbi and Zamfara States of Northern Nigeria. The strategy is aimed at reducing competition, which will invariably lead to a reduction in speed, reduction in dangerous driving, reduction in crash rate, reduction in injuries, reduction in property damages and reduction in death through road traffic crashes (RTC). This research paper presents a study focused on enhancing the safety of commercial vehicles. The background of this study highlights the alarming statistics related to commercial vehicle crashes in Nigeria with a focus on Sokoto, Kebbi and Zamfara States, which often result in significant damage to property, loss of lives, and economic costs. The significance and aims is to investigate and propose an effective strategy to enhance the safety of commercial vehicles. The study recognizes the pressing need for heightened safety measures in commercial transportation, as it impacts not only the well-being of drivers and passengers but also the overall public safety. To achieve the objectives, an examination of accident data, including causes and contributing factors, was performed to identify critical areas for improvement. The major finding of the study reveals that when competition comes into play within the realm of commercial driving, it has detrimental effects on road safety and resource management. Commercial drivers are pushed to complete their routes quickly and deliver goods on time, or they push themselves to arrive quickly for more passengers and new contracts. This competitive environment, fuelled by internal and external pressures such as tight deadlines, poverty and greed, often leads to sad endings. The study recommends that if a strategy called loading by number is integrated with other multiple safety measures, such as driver training programs, regulatory enforcement, and infrastructure improvements, commercial vehicle safety can be significantly enhanced. "Loading by Number” approach is designed to ensure that the sequence of departure of drivers from the motor park ‘A’ would be communicated to motor park officials of park ‘B’, which would be considered sequentially when giving them returning passengers, regardless of the first to arrive. In conclusion, this paper underscores the significance of improving the safety measures of commercial vehicles, as they are often larger and heavier than other vehicles on the road. Whenever they are involved in accidents, the consequences can be more severe. Commercial vehicles are also frequently involved in long-haul or interstate transportation, which means they cover longer distances and spend more time on the road. This increased exposure to driving conditions increases the probability of accidents occurring. By implementing the suggested measures, policymakers, transportation authorities, and industry stakeholders can work collectively toward ensuring a safer commercial transportation system.

Keywords: commercial, safety, strategy, transport

Procedia PDF Downloads 63

Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

Procedia PDF Downloads 358

Authors: Zhixiang Li, Shuguang Yao, Wen Ma

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Coupler rubber buffer has been widely applied on the high-speed trains and the main function of the rubber buffer is dissipating the impact energy between vehicles. The rubber buffer consists of two groups of rubbers, which are both pre-compressed and then installed into the frame body. This work focuses on the energy absorption capacity of each group of buffers particularly. The quasi-static compression tests were carried out to obtain the pre-compression force and the load-defection response of the buffers. Then a finite element (FE) model was constructed using Ls_dyna program. The rubber material was modeled with a tabulated method easily, in which no more material constants need to be fitted. The simulation results agreed with the experimental results well. Numerical study of the buffers was performed using the validated FE model and the influence of the initial pressure on the buffers was obtained. In addition, the interaction between the two groups of buffers was also investigated and the optimum distribution of the two was found.

Keywords: initial pressure, rubber buffer, simulation, tabulated method

Procedia PDF Downloads 145

Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani

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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.

Keywords: material point method, woven fabric composites, forming, material handling

Procedia PDF Downloads 181

Authors: Dogaru-Ulieru Valentin, Sălișteanu Ioan Corneliu, Ardeleanu Mihăiță Nicolae, Broscăreanu Ștefan, Sălișteanu Bogdan, Mihai Mihail

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The SiaMOTO system is a communications and data processing platform for vehicle traffic. The human factor is the most important factor in the generation of this data, as the driver is the one who dictates the trajectory of the vehicle. Like any trajectory, specific parameters refer to position, speed and acceleration. Constant knowledge of these parameters allows complex analyses. Roadways allow many vehicles to travel through their confined space, and the overlapping trajectories of several vehicles increase the likelihood of collision events, known as road accidents. Any such event has causes that lead to its occurrence, so the conditions for its occurrence are known. The human factor is predominant in deciding the trajectory parameters of the vehicle on the road, so monitoring it by knowing the events reported by the DiaMOTO device over time, will generate a guide to target any potentially high-risk driving behavior and reward those who control the driving phenomenon well. In this paper, we have focused on detailing the communication infrastructure of the DiaMOTO device with the traffic data collection server, the infrastructure through which the database that will be used for complex AI/DLM analysis is built. The central element of this description is the data string in CODEC-8 format sent by the DiaMOTO device to the SiaMOTO collection server database. The data presented are specific to a functional infrastructure implemented in an experimental model stage, by installing on a number of 50 vehicles DiaMOTO unique code devices, integrating ADAS and GPS functions, through which vehicle trajectories can be monitored 24 hours a day.

Keywords: DiaMOTO, Codec-8, ADAS, GPS, driver monitoring

Procedia PDF Downloads 78

Authors: Sergey N. Sayapin, Anatoly P. Karpenko, Suan H. Dang

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Comparative analysis of robotic vehicles for pipe inspection is presented in this paper. The promising concept of self-propelled intelligent robotic vehicle (SPIRV) based on octahedral dodekapod for inspection and operation in active branched pipelines with variable cross-sections is reasoned. SPIRV is able to move in pipeline, regardless of its spatial orientation. SPIRV can also be used to move along the outside of the pipelines as well as in space between surfaces of annular tubes. Every one of faces of the octahedral dodekapod can clamp/unclamp a thing with a closed loop surface of various forms as well as put pressure on environmental surface of contact. These properties open new possibilities for its applications in SPIRV. We examine design principles of octahedral dodekapod as future intelligent building blocks for various robotic vehicles that can self-move and self-reconfigure.

Keywords: Modular robot, octahedral dodekapod, pipe inspection robot, spatial parallel structure

Procedia PDF Downloads 501

Authors: Mehmet Ozturk, Serdal Akyuz, Halit Turan

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By the evolving technology, the nature of the war has been changed since the beginning of the history. In the first generation war, the bayonet came to the fore in battlefields; successively; in the second-generation firepower; in the third generation maneuver. Today, in the fourth-generation, fighters, sides, and even fighters’ borders are unclear; consequently, lines of the battles have lost their significance. Furthermore, the actors in the battles can be state or non-state, military, paramilitary or civilian. In order to change the balance according to their interests, parties have utilized the urban areas as warfare. The main reason for using urban areas as a battlefield is the imbalance between parties. To balance the power strength, exploiting technological developments has utmost importance. There are many newly developed technologies for urban warfare such as change in the size of the unmanned aerial vehicle, increased usage of unmanned ground vehicles (especially in supply and evacuation purposes), systems showing the behind of the wall, simulations used for educational purposes. This study will focus on the technological equipment being used for urban warfare.

Keywords: urban warfare, unmanned ground vehicles, technological developments, nature of the war

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Authors: Muhammad Faizan Rehman Qureshi, Ahmed Al-Kaisy

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Accurate estimation of traffic loads is critical for pavement and bridge design, among other transportation applications. Given the disproportional impact of heavier axle loads on pavement and bridge structures, truck and heavy vehicle traffic is expected to be a major determinant of traffic load estimation. Further, heavy vehicle traffic is also a major input in transportation planning and economic studies. The traditional method for estimating heavy vehicle traffic primarily relies on AADT estimation using Monthly Day of the Week (MDOW) adjustment factors as well as the percent heavy vehicles observed using statewide data collection programs. The MDOW factors are developed using daily and seasonal (or monthly) variation patterns for total traffic, consisting predominantly of passenger cars and other smaller vehicles. Therefore, while using these factors may yield reasonable estimates for total traffic (AADT), such estimates may involve a great deal of approximation when applied to heavy vehicle traffic. This research aims at assessing the approximation involved in estimating heavy vehicle traffic using MDOW adjustment factors for total traffic (conventional approach) along with three other methods of using MDOW adjustment factors for total trucks (class 5-13), combination-unit trucks (class 8-13), as well as adjustment factors for each vehicle class separately. Results clearly indicate that the conventional method was outperformed by the other three methods by a large margin. Further, using the most detailed and data intensive method (class-specific adjustment factors) does not necessarily yield a more accurate estimation of heavy vehicle traffic.

Keywords: traffic loads, heavy vehicles, truck traffic, adjustment factors, traffic data collection

Procedia PDF Downloads 23

Authors: Rania Alshikhe, Vinita Jindal

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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

Procedia PDF Downloads 157

Authors: Hatib Shabbir

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Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

Procedia PDF Downloads 218

Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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Authors: K. Omkar, D. Nayan

Abstract:

Rapid urbanization is one of the consequences of rapid population explosion, which has also led to massive increase in number of motorized vehicles essential for carrying out all activities needed for sustaining urban livelihood. With this increased use of motorized vehicles over the time there has also been an increase in number of accidents. Study of road network and geometric features are essential to tackle problems of road accidents in any district or town. The increase in road accidents is one of the burning issues in the present society. Records show that there is one death at every 3.7 minutes because of road accident. It has been found from the research that, accidents occur due to, mistakes of the driver (86%) followed by bad street condition (5%), mistake of pedestrian (4%), as well as technical and maintenance defects (1%). Here, case study of Ahmedabad, Gujarat is taken up where first road safety level is assessed considering various parameters. The study confined to accident characteristics of all types of vehicles. For deeper analysis, road safety index for various stretches in Ahmedabad was found out. Crash rate for same stretches was found out. Based on various parameters priority was decided so that which stretch should be look out first to minimize road accidents on that stretch and which stretch should look out last. The major findings of the study are that accident severity of Ahmedabad has increased, but accident fatality risk has decreased; thus there is need to undertake some traffic engineering measures or make some traffic rules that are strictly followed by traffic. From the above study and literature studied it is found that Ahmedabad is suffering from similar problem of accidents and injuries and deaths caused by them, after properly investigating the issue short-term and long-term solutions to minimize road accidents have been presented in this paper.

Keywords: accident severity index, accident fatality rate, accident fatality risk, accident risk, road safety index

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Authors: A. Degale Desta, Tamirat Kebamo

Abstract:

Background: Recent advances in computer vision and pattern recognition have significantly improved activity recognition through video analysis, particularly with the application of Deep Convolutional Neural Networks (CNNs). One-stage detectors now enable efficient video-based recognition by simultaneously predicting object categories and locations. Such advancements are highly relevant in educational settings where CCTV surveillance could automatically monitor academic activities, enhancing security and classroom management. However, current datasets and recognition systems lack the specific focus on campus environments necessary for practical application in these settings.Objective: This study aims to address this gap by developing a dataset and testing an automated activity recognition system specifically tailored for educational campuses. The EthioCAD dataset was created to capture various classroom activities and teacher-student interactions, facilitating reliable recognition of academic activities using deep learning models. Method: EthioCAD, a novel video-based dataset, was created with a design science research approach to encompass teacher-student interactions across three domains and 18 distinct classroom activities. Using the Roboflow AI framework, the data was processed, with 4.224 KB of frames and 33.485 MB of images managed for frame extraction, labeling, and organization. The Ultralytics YOLOv8 model was then implemented within Google Colab to evaluate the dataset’s effectiveness, achieving high mean Average Precision (mAP) scores. Results: The YOLOv8 model demonstrated robust activity recognition within campus-like settings, achieving an mAP50 of 90.2% and an mAP50-95 of 78.6%. These results highlight the potential of EthioCAD, combined with YOLOv8, to provide reliable detection and classification of classroom activities, supporting automated surveillance needs on educational campuses. Discussion: The high performance of YOLOv8 on the EthioCAD dataset suggests that automated activity recognition for surveillance is feasible within educational environments. This system addresses current limitations in campus-specific data and tools, offering a tailored solution for academic monitoring that could enhance the effectiveness of CCTV systems in these settings. Conclusion: The EthioCAD dataset, alongside the YOLOv8 model, provides a promising framework for automated campus activity recognition. This approach lays the groundwork for future advancements in CCTV-based educational surveillance systems, enabling more refined and reliable monitoring of classroom activities.

Keywords: deep CNN, EthioCAD, deep learning, YOLOv8, activity recognition

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Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Atieh Asgari Toorzani

Abstract:

Pedestrians are the most vulnerable road users since they do not have a protective shell. One of the most common collisions for them is pedestrian-vehicle at intersections. In order to develop appropriate countermeasures to improve safety for them, researches have to be conducted to identify the factors that affect the risk of getting involved in such collisions. More specifically, this study investigates factors such as the influence of walking alone or having a baby while crossing the street, the observable age of pedestrian, the speed of pedestrians and the speed of approaching vehicles on risk perception of pedestrians. A nested logit model was used for modeling the behavioral structure of pedestrians. The results show that the presence of more lanes at intersections and not being alone especially having a baby while crossing, decrease the probability of taking a risk among pedestrians. Also, it seems that teenagers show more risky behaviors in crossing the street in comparison to other age groups. Also, the speed of approaching vehicles was considered significant. The probability of risk taking among pedestrians decreases by increasing the speed of approaching vehicle in both the first and the second lanes of crossings.

Keywords: pedestrians, intersection, nested logit, risk

Procedia PDF Downloads 186

Authors: Shahab Uddin, Kazi M. Uddin, Hamamah Sadiqa

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The paper deals with the Banghabandhu Multipurpose Bridge (BMB), the 11th longest bridge in the world was constructed in 1998 aimed at contributing to promote economic development in Bangladesh. In recent years, however, the high incidence of traffic accidents and injuries at the bridge sites looms as a great safety concern. Investigation into the derailment of nine bogies out of thirteen of Dinajpur-bound intercity train ‘Drutajan Express ’were derailed and inclined on the Banghabandhu Multipurpose Bridge on 28 April 2014. The train accident in Bridge will be deep concern for both structural safety of bridge and people than other vehicles accident. In this study we analyzed the disaster probability of the Banghabandhu Multipurpose Bridge for accidents by checking the fitness of Bridge structure. We found that train accident impact is more risky than other vehicles accidents. We also found that socio-economic impact on Bangladesh will be deep concerned.

Keywords: train accident, derailment, disaster, socio-economic

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Authors: Mona Lisa M. Oliveira, Nara A. Policarpo, Ana Luiza B. P. Barros, Carla A. Silva

Abstract:

Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH₃ slips even more. Ammonia (NH₃) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH₃ is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH₃ via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH₃-slip emission factors for different driving conditions and patterns. The proposed model generates high NH₃slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH₃ to the urban atmosphere.

Keywords: ammonia slip, neural-network, vehicles emissions, SCR-NOx

Procedia PDF Downloads 213