Search results for: automated vehicle
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2162

Search results for: automated vehicle

1982 Heavy Vehicles Crash Injury Severity at T-Intersections

Authors: Sivanandan Balakrishnan, Sara Moridpour, Richard Tay

Abstract:

Heavy vehicles make a significant contribution to many developed economies, including Australia, because they are a major means of transporting goods within these countries. With the increase in road freight, there will be an increase in the heavy vehicle traffic proportion, and consequently, an increase in the possibility of collisions involving heavy vehicles. Crashes involving heavy vehicles are a major road safety concern because of the higher likelihood of fatal and serious injury, especially to any small vehicle occupant involved. The primary objective of this research is to identify the factors influencing injury severity to occupants in vehicle collisions involving heavy vehicle at T- intersection using a binary logit model in Victoria, Australia. Our results show that the factors influencing injury severity include occupants' gender, age and restraint use. Also, vehicles' type, movement, point-of-impact and damage, time-of-day, day-of-week and season, higher percentage of trucks in traffic volume, hit pedestrians, number of occupants involved and type of collisions are associated with severe injury.

Keywords: binary logit model, heavy vehicle, injury severity, T-intersections

Procedia PDF Downloads 361
1981 Bias Prevention in Automated Diagnosis of Melanoma: Augmentation of a Convolutional Neural Network Classifier

Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

Abstract:

Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

Procedia PDF Downloads 175
1980 A Convolutional Neural Network Based Vehicle Theft Detection, Location, and Reporting System

Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

Abstract:

One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

Procedia PDF Downloads 125
1979 Research on Transmission Parameters Determination Method Based on Dynamic Characteristic Analysis

Authors: Baoshan Huang, Fanbiao Bao, Bing Li, Lianghua Zeng, Yi Zheng

Abstract:

Parameter control strategy based on statistical characteristics can analyze the choice of the transmission ratio of an automobile transmission. According to the difference of the transmission gear, the number and spacing of the gear can be determined. Transmission ratio distribution of transmission needs to satisfy certain distribution law. According to the statistic characteristics of driving parameters, the shift control strategy of the vehicle is analyzed. CVT shift schedule adjustment algorithm based on statistical characteristic parameters can be seen from the above analysis, if according to the certain algorithm to adjust the size of, can adjust the target point are in the best efficiency curve and dynamic curve between the location, to alter the vehicle characteristics. Based on the dynamic characteristics and the practical application of the vehicle, this paper presents the setting scheme of the transmission ratio.

Keywords: vehicle dynamics, transmission ratio, transmission parameters, statistical characteristics

Procedia PDF Downloads 365
1978 Analysis of Brake System for Vehicle Off-Road

Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale, José Ubiragi de Lima Mendes

Abstract:

In elapsing of the years it elaborates automobile it is developing automobiles more and more modern that, every year, the vehicles recently of the assembly lines, practically they push for the past produced models there is very little time. Those innovations didn't also pass unperceived in 0respect the safety of the vehicles. It is in this development apprenticeship the brakes systems equipped more and more with resources sophisticated. In that way, before of that context, this research tried to project a brake system for a vehicle off-road and to analyze your acting as the brakes efficiency: distances traveled and time, concluding with possible improvements in the system.

Keywords: brakes system, off-road, vehicle acting, automotive and mechanical engineering

Procedia PDF Downloads 451
1977 Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

Authors: Ying Su, Morgan C. Wang

Abstract:

Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

Procedia PDF Downloads 46
1976 Solar Powered Front Wheel Drive (FWD) Electric Trike: An Innovation

Authors: Michael C. Barbecho, Romeo B. Morcilla

Abstract:

This study focused on the development of a solar powered front wheel drive electric trike for personal use and short distance travel, utilizing solar power and a variable speed transmission to adapt in places where varying road grades and unavailability of plug-in charging stations are of great problems. The actual performance of the vehicle was measured in terms of duration of charging using solar power, distance travel and battery power duration, top speed developed at full power, and load capacity. This project followed the research and development process which involved planning, designing, construction, and testing. Solar charging tests revealed that the vehicle requires 6 to 8 hours sunlight exposure to fully charge the batteries. At full charge, the vehicle can travel 35 km utilizing battery power down to 42%. Vehicle showed top speed of 25 kph at 0 to 3% road grade carrying a maximum load of 122 kg. The maximum climbing grade was 23% with the vehicle carrying a maximum load of 122 kg. Technically the project was feasible and can be a potential model for possible conversion of traditional Philippine made “pedicabs” and gasoline engine powered tricycle into modern electric vehicles. Moreover, it has several technical features and advantages over a commercialized electric vehicle such as the use solar charging system and variable speed power transmission and front drive power train for adaptability in any road gradient.

Keywords: electric vehicle, solar vehicles, front drive, solar, solar power

Procedia PDF Downloads 545
1975 A Mechanism of Reusable, Portable, and Reliable Script Generator on Android

Authors: Kuei-Chun Liu, Yu-Yu Lai, Ching-Hong Wu

Abstract:

A good automated testing tool could reduce as much as possible the manual work done by testers. Traditional record-replay testing tool provides an automated testing solution by recording mouse coordinates as test scripts, but it will be easily broken if any change of resolutions. Therefore, more and more testers design multiple test scripts to automate the testing process for different devices. In order to improve the traditional record-replay approach and reduce the effort that the testers spending on writing test scripts, we propose an approach for generating the Android application test scripts based on accessibility service without connecting to a computer. This approach simulates user input actions and replays them correctly even at the different conditions such as the internet connection is unstable when the device under test, the different resolutions on Android devices. In this paper, we describe how to generate test scripts automatically and make a comparison with existing tools for Android such as Robotium, Appium, UIAutomator, and MonkeyTalk.

Keywords: accessibility service, Appium, automated testing, MonkeyTalk, Robotium, testing, UIAutomator

Procedia PDF Downloads 345
1974 Shared Versus Pooled Automated Vehicles: Exploring Behavioral Intentions Towards On-Demand Automated Vehicles

Authors: Samira Hamiditehrani

Abstract:

Automated vehicles (AVs) are emerging technologies that could potentially offer a wide range of opportunities and challenges for the transportation sector. The advent of AV technology has also resulted in new business models in shared mobility services where many ride hailing and car sharing companies are developing on-demand AVs including shared automated vehicles (SAVs) and pooled automated vehicles (Pooled AVs). SAVs and Pooled AVs could provide alternative shared mobility services which encourage sustainable transport systems, mitigate traffic congestion, and reduce automobile dependency. However, the success of on-demand AVs in addressing major transportation policy issues depends on whether and how the public adopts them as regular travel modes. To identify conditions under which individuals may adopt on-demand AVs, previous studies have applied human behavior and technology acceptance theories, where Theory of Planned Behavior (TPB) has been validated and is among the most tested in on-demand AV research. In this respect, this study has three objectives: (a) to propose and validate a theoretical model for behavioral intention to use SAVs and Pooled AVs by extending the original TPB model; (b) to identify the characteristics of early adopters of SAVs, who prefer to have a shorter and private ride, versus prospective users of Pooled AVs, who choose more affordable but longer and shared trips; and (c) to investigate Canadians’ intentions to adopt on-demand AVs for regular trips. Toward this end, this study uses data from an online survey (n = 3,622) of workers or adult students (18 to 75 years old) conducted in October and November 2021 for six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa, Montreal, Calgary, and Hamilton. To accomplish the goals of this study, a base bivariate ordered probit model, in which both SAV and Pooled AV adoptions are estimated as ordered dependent variables, alongside a full structural equation modeling (SEM) system are estimated. The findings of this study indicate that affective motivations such as attitude towards AV technology, perceived privacy, and subjective norms, matter more than sociodemographic and travel behavior characteristic in adopting on-demand AVs. Also, the results of second objective provide evidence that although there are a few affective motivations, such as subjective norms and having ample knowledge, that are common between early adopters of SAVs and PooledAVs, many examined motivations differ among SAV and Pooled AV adoption factors. In other words, motivations influencing intention to use on-demand AVs differ among the service types. Likewise, depending on the types of on-demand AVs, the sociodemographic characteristics of early adopters differ significantly. In general, findings paint a complex picture with respect to the application of constructs from common technology adoption models to the study of on-demand AVs. Findings from the final objective suggest that policymakers, planners, the vehicle and technology industries, and the public at large should moderate their expectations that on-demand AVs may suddenly transform the entire transportation sector. Instead, this study suggests that SAVs and Pooled AVs (when they entire the Canadian market) are likely to be adopted as supplementary mobility tools rather than substitutions for current travel modes

Keywords: automated vehicles, Canadian perception, theory of planned behavior, on-demand AVs

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1973 3D-Vehicle Associated Research Fields for Smart City via Semantic Search Approach

Authors: Haluk Eren, Mucahit Karaduman

Abstract:

This paper presents 15-year trends for scientific studies in a scientific database considering 3D and vehicle words. Two words are selected to find their associated publications in IEEE scholar database. Both of keywords are entered individually for the years 2002, 2012, and 2016 on the database to identify the preferred subjects of researchers in same years. We have classified closer research fields after searching and listing. Three years (2002, 2012, and 2016) have been investigated to figure out progress in specified time intervals. The first one is assumed as the initial progress in between 2002-2012, and the second one is in 2012-2016 that is fast development duration. We have found very interesting and beneficial results to understand the scholars’ research field preferences for a decade. This information will be highly desirable in smart city-based research purposes consisting of 3D and vehicle-related issues.

Keywords: Vehicle, three-dimensional, smart city, scholarly search, semantic

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1972 Chromatography Study of Fundamental Properties of Medical Radioisotope Astatine-211

Authors: Evgeny E. Tereshatov

Abstract:

Astatine-211 is considered one of the most promising radionuclides for Targeted Alpha Therapy. In order to develop reliable procedures to label biomolecules and utilize efficient delivery vehicle principles, one should understand the main chemical characteristics of astatine. The short half-life of 211At (~7.2 h) and absence of any stable isotopes of this element are limiting factors towards studying the behavior of astatine. Our team has developed a procedure for rapid and efficient isolation of astatine from irradiated bismuth material in nitric acid media based on 3-octanone and 1-octanol extraction chromatography resins. This process has been automated and it takes 20 min from the beginning of the target dissolution to the At-211 fraction elution. Our next step is to consider commercially available chromatography resins and their applicability in astatine purification in the same media. Results obtained along with the corresponding sorption mechanisms will be discussed.

Keywords: astatine-211, chromatography, automation, mechanism, radiopharmaceuticals

Procedia PDF Downloads 65
1971 GA3C for Anomalous Radiation Source Detection

Authors: Chia-Yi Liu, Bo-Bin Xiao, Wen-Bin Lin, Hsiang-Ning Wu, Liang-Hsun Huang

Abstract:

In order to reduce the risk of radiation damage that personnel may suffer during operations in the radiation environment, the use of automated guided vehicles to assist or replace on-site personnel in the radiation environment has become a key technology and has become an important trend. In this paper, we demonstrate our proof of concept for autonomous self-learning radiation source searcher in an unknown environment without a map. The research uses GPU version of Asynchronous Advantage Actor-Critic network (GA3C) of deep reinforcement learning to search for radiation sources. The searcher network, based on GA3C architecture, has self-directed learned and improved how search the anomalous radiation source by training 1 million episodes under three simulation environments. In each episode of training, the radiation source position, the radiation source intensity, starting position, are all set randomly in one simulation environment. The input for searcher network is the fused data from a 2D laser scanner and a RGB-D camera as well as the value of the radiation detector. The output actions are the linear and angular velocities. The searcher network is trained in a simulation environment to accelerate the learning process. The well-performance searcher network is deployed to the real unmanned vehicle, Dashgo E2, which mounts LIDAR of YDLIDAR G4, RGB-D camera of Intel D455, and radiation detector made by Institute of Nuclear Energy Research. In the field experiment, the unmanned vehicle is enable to search out the radiation source of the 18.5MBq Na-22 by itself and avoid obstacles simultaneously without human interference.

Keywords: deep reinforcement learning, GA3C, source searching, source detection

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1970 Improving the Global Competitiveness of SMEs by Logistics Transportation Management: Case Study Chicken Meat Supply Chain

Authors: P. Vanichkobchinda

Abstract:

The Logistics Transportation techniques, Open Vehicle Routing (OVR) is an approach toward transportation cost reduction, especially for long distance pickup and delivery nodes. The outstanding characteristic of OVR is that the route starting node and ending node are not necessary the same as in typical vehicle routing problems. This advantage enables the routing to flow continuously and the vehicle does not always return to its home base. This research aims to develop a heuristic for the open vehicle routing problem with pickup and delivery under time window and loading capacity constraints to minimize the total distance. The proposed heuristic is developed based on the Insertion method, which is a simple method and suitable for the rapid calculation that allows insertion of the new additional transportation requirements along the original paths. According to the heuristic analysis, cost comparisons between the proposed heuristic and companies are using method, nearest neighbor method show that the insertion heuristic. Moreover, the proposed heuristic gave superior solutions in all types of test problems. In conclusion, the proposed heuristic can effectively and efficiently solve the open vehicle routing. The research indicates that the improvement of new transport's calculation and the open vehicle routing with "Insertion Heuristic" represent a better outcome with 34.3 percent in average. in cost savings. Moreover, the proposed heuristic gave superior solutions in all types of test problems. In conclusion, the proposed heuristic can effectively and efficiently solve the open vehicle routing.

Keywords: business competitiveness, cost reduction, SMEs, logistics transportation, VRP

Procedia PDF Downloads 660
1969 Dry Friction Occurring in the Suspensions for Passive and Switchable Damper Systems and Its Effect on Ride Comfort

Authors: Aref M. A. Soliman, Mahmoud A. Hassan

Abstract:

In all vehicle suspension, there is a dry friction. One of the various active suspensions, which have been shown to have considerable practical potential, is a switchable damper suspension system. In this paper, vehicle ride comfort for the passive and switchable damper suspension systems as affected by the value of frictional force generated in springs is discussed. A mathematical model of a quarter vehicle model for two setting switchable damper suspension system with dry friction force is developed to evaluate vehicle ride comfort in terms of suspension performance criteria. The vehicle itself is treated as a rigid body undergoing vertical motions. Comparisons between passive and switchable damper suspensions systems with dry friction force in terms of ride performance are also discussed. The results showed that the ride comfort for the passive and switchable damper suspension systems was deteriorated due to dry friction occurring in the suspensions. The two setting switchable damper with and without dry friction force gives better ride improvements compared with the passive suspension system. Also, the obtained results show an optimum value of damping ratio of the passive suspension system.

Keywords: ride comfort, dry friction, switchable damper, passive suspension

Procedia PDF Downloads 336
1968 Lubrication Performance of Multi-Level Gear Oil in a Gasoline Engine

Authors: Feng-Tsai Weng, Dong- Syuan Cai, Tsochu-Lin

Abstract:

A vehicle gasoline engine converts gasoline into power so that the car can move, and lubricants are important for engines and also gear boxes. Manufacturers have produced numbers of engine oils, and gear oils for engines and gear boxes to SAE International Standards. Some products not only can improve the lubrication of both the engine and gear box but also can raise power of vehicle this can be easily seen in the advertisement declared by the manufacturers. To observe the lubrication performance, a multi-leveled (heavy duty) gear oil was added to a gasoline engine as the oil in the vehicle. The oil was checked at about every 10,000 kilometers. The engine was detailed disassembled, cleaned, and parts were measured. The wear of components of the engine parts were checked and recorded finally. Based on the experiment results, some gear oil seems possible to be used as engine oil in particular vehicles. Vehicle owners should change oil periodically in about every 6,000 miles (or 10,000 kilometers). Used car owners may change engine oil in even longer distance.

Keywords: multi-level gear oil, engine oil, viscosity, abrasion

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1967 Investigation on the Bogie Pseudo-Hunting Motion of a Reduced-Scale Model Railway Vehicle Running on Double-Curved Rails

Authors: Barenten Suciu, Ryoichi Kinoshita

Abstract:

In this paper, an experimental and theoretical study on the bogie pseudo-hunting motion of a reduced-scale model railway vehicle, running on double-curved rails, is presented. Since the actual bogie hunting motion, occurring for real railway vehicles running on straight rails at high travelling speeds, cannot be obtained in laboratory conditions, due to the speed and wavelength limitations, a pseudo- hunting motion was induced by employing double-curved rails. Firstly, the test rig and the experimental procedure are described. Then, a geometrical model of the double-curved rails is presented. Based on such model, the variation of the carriage rotation angle relative to the bogies and the working conditions of the yaw damper are clarified. Vibration spectra recorded during vehicle travelling, on straight and double-curved rails, are presented and interpreted based on a simple vibration model of the railway vehicle. Ride comfort of the vehicle is evaluated according to the ISO 2631 standard, and also by using some particular frequency weightings, which account for the discomfort perceived during the reading and writing activities. Results obtained in this work are useful for the adequate design of the yaw dampers, which are used to attenuate the lateral vibration of the train car bodies.

Keywords: double-curved rail, octave analysis, vibration model, ride comfort, railway vehicle

Procedia PDF Downloads 288
1966 Light Car Assisted by PV Panels

Authors: Soufiane Benoumhani, Nadia Saifi, Boubekeur Dokkar, Mohamed Cherif Benzid

Abstract:

This work presents the design and simulation of electric equipment for a hybrid solar vehicle. The new drive train of this vehicle is a parallel hybrid system which means a vehicle driven by a great percentage of an internal combustion engine with 49.35 kW as maximal power and electric motor only as assistance when is needed. This assistance is carried out on the rear axle by a single electric motor of 7.22 kW as nominal power. The motor is driven by 12 batteries connecting in series, which are charged by three PV panels (300 W) installed on the roof and hood of the vehicle. The individual components are modeled and simulated by using the Matlab Simulink environment. The whole system is examined under different load conditions. The reduction of CO₂ emission is obtained by reducing fuel consumption. With the use of this hybrid system, fuel consumption can be reduced from 6.74 kg/h to 5.56 kg/h when the electric motor works at 100 % of its power. The net benefit of the system reaches 1.18 kg/h as fuel reduction at high values of power and torque.

Keywords: light car, hybrid system, PV panel, electric motor

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1965 The Development of an Automated Computational Workflow to Prioritize Potential Resistance Variants in HIV Integrase Subtype C

Authors: Keaghan Brown

Abstract:

The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

Procedia PDF Downloads 36
1964 A Prediction Model Using the Price Cyclicality Function Optimized for Algorithmic Trading in Financial Market

Authors: Cristian Păuna

Abstract:

After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

Procedia PDF Downloads 153
1963 Retrofitted Semi-Active Suspension System for a Eelectric Model Vehicle

Authors: Shiuh-Jer Huang, Yun-Han Yeh

Abstract:

A 40 steps manual adjusting shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system for a four-wheel drive electric vehicle. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. A fuzzy logic controller was designed to derive appropriate damping target based on vehicle running condition for semi-active suspension system to follow. The damping ratio control of each wheel axis suspension system is executed with a robust fuzzy sliding mode controller (FSMC). Different road surface conditions are chosen to evaluate the control performance of this semi-active suspension system based on wheel axis acceleration signal.

Keywords: semi-active suspension, electric vehicle, fuzzy sliding mode control, accelerometer

Procedia PDF Downloads 450
1962 Investigating Effects of Vehicle Speed and Road PSDs on Response of a 35-Ton Heavy Commercial Vehicle (HCV) Using Mathematical Modelling

Authors: Amal G. Kurian

Abstract:

The use of mathematical modeling has seen a considerable boost in recent times with the development of many advanced algorithms and mathematical modeling capabilities. The advantages this method has over other methods are that they are much closer to standard physics theories and thus represent a better theoretical model. They take lesser solving time and have the ability to change various parameters for optimization, which is a big advantage, especially in automotive industry. This thesis work focuses on a thorough investigation of the effects of vehicle speed and road roughness on a heavy commercial vehicle ride and structural dynamic responses. Since commercial vehicles are kept in operation continuously for longer periods of time, it is important to study effects of various physical conditions on the vehicle and its user. For this purpose, various experimental as well as simulation methodologies, are adopted ranging from experimental transfer path analysis to various road scenario simulations. To effectively investigate and eliminate several causes of unwanted responses, an efficient and robust technique is needed. Carrying forward this motivation, the present work focuses on the development of a mathematical model of a 4-axle configuration heavy commercial vehicle (HCV) capable of calculating responses of the vehicle on different road PSD inputs and vehicle speeds. Outputs from the model will include response transfer functions and PSDs and wheel forces experienced. A MATLAB code will be developed to implement the objectives in a robust and flexible manner which can be exploited further in a study of responses due to various suspension parameters, loading conditions as well as vehicle dimensions. The thesis work resulted in quantifying the effect of various physical conditions on ride comfort of the vehicle. An increase in discomfort is seen with velocity increase; also the effect of road profiles has a considerable effect on comfort of the driver. Details of dominant modes at each frequency are analysed and mentioned in work. The reduction in ride height or deflection of tire and suspension with loading along with load on each axle is analysed and it is seen that the front axle supports a greater portion of vehicle weight while more of payload weight comes on fourth and third axles. The deflection of the vehicle is seen to be well inside acceptable limits.

Keywords: mathematical modeling, HCV, suspension, ride analysis

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1961 Concept and Design of a Biomimetic Single-Wing Micro Aerial Vehicle (MAV)

Authors: S. Thomas, D. Ho, A. Kerroux, L. Lixi, N. Rackham, S. Rosenfeld

Abstract:

In this first paper, the different concepts and designs to build a single-wing MAV are discussed. Six scratch-building prototypes using three different designs have been tested regarding sufficient lift and weight distribution, of which various configurations were explored. Samare prototypes achieved wireless control over the motor and flap whilst obtaining data from the IMU, though obtaining an increase in lift was the key issue due to insufficient thrust. The final prototype was able to demonstrate an improvement in weight distribution.

Keywords: SAMARE, micro aerial vehicle (MAV), unmanned aerial vehicle (UAV), mono-copter, single-wing, mono-wing, flight control, aerofoil, lift

Procedia PDF Downloads 424
1960 Tuning for a Small Engine with a Supercharger

Authors: Shinji Kajiwara, Tadamasa Fukuoka

Abstract:

The formula project of Kinki University has been involved in the student Formula SAE of Japan (JSAE) since the second year the competition was held. The vehicle developed in the project uses a ZX-6R engine, which has been manufactured by Kawasaki Heavy Industries for the JSAE competition for the eighth time. The limited performance of the concept vehicle was improved through the development of a power train. The supercharger loading, engine dry sump, and engine cooling management of the vehicle were also enhanced. The supercharger loading enabled the vehicle to achieve a maximum output of 59.6 kW (80.6 PS)/9000 rpm and a maximum torque of 70.6 Nm (7.2 kgf m)/8000 rpm. We successfully achieved 90% of the engine’s torque band (4000–10000 rpm) with 50% of the revolutions in regular engine use (2000–12000 rpm). Using a dry sump system, we periodically managed hydraulic pressure during engine operation. A system that controls engine stoppage when hydraulic pressure falls was also constructed. Using the dry sump system at 80 mm reduced the required engine load and the vehicle’s center of gravity. Even when engine motion was suspended by the electromotive force exerted by the water pump, the circulation of cooling water was still possible. These findings enabled us to create a cooling system in accordance with the requirements of the competition.

Keywords: engine, combustion, cooling system, numerical simulation, power, torque, mechanical super charger

Procedia PDF Downloads 277
1959 Performance Improvement of Electric Vehicle Using K - Map Constructed Rule Based Energy Management Strategy for Battery/Ultracapacitor Hybrid Energy Storage System

Authors: Jyothi P. Phatak, L. Venkatesha, C. S. Raviprasad

Abstract:

The performance improvement of Hybrid Energy Storage System (HESS) in Electric Vehicle (EV) has been in discussion over the last decade. The important issues in terms of performance parameters addressed are, range of vehicle and battery (BA) peak current. Published literature has either addressed battery peak current reduction or range improvement in EV. Both the issues have not been specifically discussed and analyzed. This paper deals with both range improvement in EV and battery peak current reduction by applying a new Karnaugh Map (K-Map) constructed rule based energy management strategy to proposed HESS. The strategy allows Ultracapacitor (UC) to assist battery when the vehicle accelerates there by reducing the burden on battery. Simulation is carried out for various operating modes of EV considering both urban and highway driving conditions. Simulation is done for different values of UC by keeping battery rating constant for each driving cycle and results are presented. Feasible value of UC is selected based on simulation results. The results of proposed HESS show an improvement in performance parameters compared to Battery only Energy Storage System (BESS). Battery life is improved to considerable extent and there is an overall development in the performance of electric vehicle.

Keywords: electric vehicle, PID controller, energy management strategy, range, battery current, ultracapacitor

Procedia PDF Downloads 83
1958 Enhancing the Recruitment Process through Machine Learning: An Automated CV Screening System

Authors: Kaoutar Ben Azzou, Hanaa Talei

Abstract:

Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

Procedia PDF Downloads 23
1957 Robotic Arm-Automated Spray Painting with One-Shot Object Detection and Region-Based Path Optimization

Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

Abstract:

Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

Procedia PDF Downloads 43
1956 Optimal Delivery of Two Similar Products to N Ordered Customers

Authors: Epaminondas G. Kyriakidis, Theodosis D. Dimitrakos, Constantinos C. Karamatsoukis

Abstract:

The vehicle routing problem (VRP) is a well-known problem in Operations Research and has been widely studied during the last fifty-five years. The context of the VRP is that of delivering products located at a central depot to customers who are scattered in a geographical area and have placed orders for these products. A vehicle or a fleet of vehicles start their routes from the depot and visit the customers in order to satisfy their demands. Special attention has been given to the capacitated VRP in which the vehicles have limited carrying capacity of the goods that must be delivered. In the present work, we present a specific capacitated stochastic vehicle routing problem which has realistic applications to distributions of materials to shops or to healthcare facilities or to military units. A vehicle starts its route from a depot loaded with items of two similar but not identical products. We name these products, product 1 and product 2. The vehicle must deliver the products to N customers according to a predefined sequence. This means that first customer 1 must be serviced, then customer 2 must be serviced, then customer 3 must be serviced and so on. The vehicle has a finite capacity and after servicing all customers it returns to the depot. It is assumed that each customer prefers either product 1 or product 2 with known probabilities. The actual preference of each customer becomes known when the vehicle visits the customer. It is also assumed that the quantity that each customer demands is a random variable with known distribution. The actual demand is revealed upon the vehicle’s arrival at customer’s site. The demand of each customer cannot exceed the vehicle capacity and the vehicle is allowed during its route to return to the depot to restock with quantities of both products. The travel costs between consecutive customers and the travel costs between the customers and the depot are known. If there is shortage for the desired product, it is permitted to deliver the other product at a reduced price. The objective is to find the optimal routing strategy, i.e. the routing strategy that minimizes the expected total cost among all possible strategies. It is possible to find the optimal routing strategy using a suitable stochastic dynamic programming algorithm. It is also possible to prove that the optimal routing strategy has a specific threshold-type structure, i.e. it is characterized by critical numbers. This structural result enables us to construct an efficient special-purpose dynamic programming algorithm that operates only over those routing strategies having this structure. The findings of the present study lead us to the conclusion that the dynamic programming method may be a very useful tool for the solution of specific vehicle routing problems. A problem for future research could be the study of a similar stochastic vehicle routing problem in which the vehicle instead of delivering, it collects products from ordered customers.

Keywords: collection of similar products, dynamic programming, stochastic demands, stochastic preferences, vehicle routing problem

Procedia PDF Downloads 237
1955 Eco-Drive Predictive Analytics

Authors: Sharif Muddsair, Eisels Martin, Giesbrecht Eugenie

Abstract:

With development of society increase the demand for the movement of people also increases gradually. The various modes of the transport in different extent which expat impacts, which depends on mainly technical-operating conditions. The up-to-date telematics systems provide the transport industry a revolutionary. Appropriate use of these systems can help to substantially improve the efficiency. Vehicle monitoring and fleet tracking are among services used for improving efficiency and effectiveness of utility vehicle. There are many telematics systems which may contribute to eco-driving. Generally, they can be grouped according to their role in driving cycle. • Before driving - eco-route selection, • While driving – Advanced driver assistance, • After driving – remote analysis. Our point of interest is regulated in third point [after driving – remote analysis]. TS [Telematics-system] make it possible to record driving patterns in real time and analysis the data later on, So that driver- classification-specific hints [fast driver, slow driver, aggressive driver…)] are given to imitate eco-friendly driving style. Together with growing number of vehicle and development of information technology, telematics become an ‘active’ research subject in IT and the car industry. Telematics has gone a long way from providing navigation solution/assisting the driver to become an integral part of the vehicle. Today’s telematics ensure safety, comfort and become convenience of the driver.

Keywords: internet of things, iot, connected vehicle, cv, ts, telematics services, ml, machine learning

Procedia PDF Downloads 274
1954 Cross-Layer Design of Event-Triggered Adaptive OFDMA Resource Allocation Protocols with Application to Vehicle Clusters

Authors: Shaban Guma, Naim Bajcinca

Abstract:

We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes.

Keywords: consensus, cross-layer, distributed, event-triggered, multi-vehicle, protocol, resource, OFDMA, wireless

Procedia PDF Downloads 303
1953 Methodology to Affirm Driver Engagement in Dynamic Driving Task (DDT) for a Level 2 Adas Feature

Authors: Praneeth Puvvula

Abstract:

Autonomy in has become increasingly common in modern automotive cars. There are 5 levels of autonomy as defined by SAE. This paper focuses on a SAE level 2 feature which, by definition, is able to control the vehicle longitudinally and laterally at the same time. The system keeps the vehicle centred with in the lane by detecting the lane boundaries while maintaining the vehicle speed. As with the features from SAE level 1 to level 3, the primary responsibility of dynamic driving task lies with the driver. This will need monitoring techniques to ensure the driver is always engaged even while the feature is active. This paper focuses on the these techniques, which would help the safe usage of the feature and provide appropriate warnings to the driver.

Keywords: autonomous driving, safety, adas, automotive technology

Procedia PDF Downloads 56