Search results for: autonomous vehicle control

Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Youtao Gao, Bingyu Jin, Tanran Zhao, Bo Xu

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The history of satellite navigation can be dated back to the 1960s. From the U.S. Transit system and the Russian Tsikada system to the modern Global Positioning System (GPS) and the Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS), performance of satellite navigation has been greatly improved. Nowadays, the navigation accuracy and coverage of these existing systems have already fully fulfilled the requirement of near-Earth users, but these systems are still beyond the reach of deep space targets. Due to the renewed interest in space exploration, a novel high-precision satellite navigation system is becoming even more important. The increasing demand for such a deep space navigation system has contributed to the emergence of a variety of new constellation architectures, such as the Lunar Global Positioning System. Apart from a Walker constellation which is similar to the one adopted by GPS on Earth, a novel constellation architecture which consists of libration point satellites in the Earth-Moon system is also available to construct the lunar navigation system, which can be called accordingly, the libration point satellite navigation system. The concept of using Earth-Moon libration point satellites for lunar navigation was first proposed by Farquhar and then followed by many other researchers. Moreover, due to the special characteristics of Libration point orbits, an autonomous orbit determination technique, which is called ‘Liaison navigation’, can be adopted by the libration point satellites. Using only scalar satellite-to-satellite tracking data, both the orbits of the user and libration point satellites can be determined autonomously. In this way, the extensive Earth-based tracking measurement can be eliminated, and an autonomous satellite navigation system can be developed for future space exploration missions. The method of state estimate is an unnegligible factor which impacts on the orbit determination accuracy besides type of orbit, initial state accuracy and measurement accuracy. We apply the extended Kalman filter(EKF) and the unscented Kalman filter(UKF) to determinate the orbits of Lagrangian navigation satellites. The autonomous orbit determination errors are compared. The simulation results illustrate that UKF can improve the accuracy and z-axis convergence to some extent.

Keywords: extended Kalman filter, autonomous orbit determination, unscented Kalman filter, navigation constellation

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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

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Authors: Sharif Muddsair, Eisels Martin, Giesbrecht Eugenie

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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

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Authors: Paulo Fernando Silva Filho, Elcio Hideiti Shiguemori

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The selection of specific landmarks for an Unmanned Aerial Vehicles’ Visual Navigation systems based on Automatic Landmark Recognition has significant influence on the precision of the system’s estimated position. At the same time, manual selection of the landmarks does not guarantee a high recognition rate, which would also result on a poor precision. This work aims to develop an automatic landmark selection that will take the image of the flight area and identify the best landmarks to be recognized by the Visual Navigation Landmark Recognition System. The criterion to select a landmark is based on features detected by ORB or AKAZE and edges information on each possible landmark. Results have shown that disposition of possible landmarks is quite different from the human perception.

Keywords: clustering, edges, feature points, landmark selection, X-means

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Authors: N. Gayathri Devi, K. Batri

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The advent of technology has increased the traffic hazards and the road accidents take place. Collision detection system in automobile aims at reducing or mitigating the severity of an accident. This project aims at avoiding Vehicle head on collision by means of collision detection algorithm. This collision detection algorithm predicts the collision and the avoidance or minimization have to be done within few seconds on confirmation. Under critical situation collision minimization is made possible by turning the vehicle to the desired turn radius so that collision impact can be reduced. In order to avoid the collision completely, the turning of the vehicle should be achieved at reduced speed in order to maintain the stability.

Keywords: collision avoidance system, time to collision, time to turn, turn radius

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz

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Performance of any vehicle can be predicted by its design/modeling and optimization. Design optimization leads to efficient performance. Followed by horizontal launch, the air launch re-entry vehicle undergoes a launch maneuver by introducing a carefully selected angle of attack profile. This angle of attack profile is the basic element to complete a specified mission. Flight program of said vehicle is optimized under the constraints of the maximum allowed angle of attack, lateral and axial loads and with the objective of reaching maximum altitude. The main focus of this study is the endo-atmospheric phase of the ascent trajectory. A three degrees of freedom trajectory model is simulated in MATLAB. The optimization process uses evolutionary algorithm, because of its robustness and efficient capacity to explore the design space in search of the global optimum. Evolutionary Algorithm based trajectory optimization also offers the added benefit of being a generalized method that may work with continuous, discontinuous, linear, and non-linear performance matrix. It also eliminates the requirement of a starting solution. Optimization is particularly beneficial to achieve maximum advantage without increasing the computational cost and affecting the output of the system. For the case of launch vehicles we are immensely anxious to achieve maximum performance and efficiency under different constraints. In a launch vehicle, flight program means the prescribed variation of vehicle pitching angle during the flight which has substantial influence reachable altitude and accuracy of orbit insertion and aerodynamic loading. Results reveal that the angle of attack profile significantly affects the performance of the vehicle.

Keywords: endo-atmospheric, evolutionary algorithm, efficient performance, optimization process

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Authors: Khalil Aghapouramin, Mostafa Ranjbar

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Run- to- Run (R2 R) control was developed in order to monitor and control different semiconductor manufacturing processes based upon the fundamental engineering frameworks. This technology allows rectification in the optimum direction. This control always had a significant potency in which was appeared in a variety of processes. The term run to run refers to the case where the act of control would take with the aim of getting batches of silicon wafers which produced in a manufacturing process. In the present work, a brief review about run-to-run control investigated which mainly is effective in the manufacturing process.

Keywords: Run-to-Run (R2R) control, manufacturing, process in engineering, manufacturing controls

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Authors: Do Chi Thanh, Dang Ngoc Huy

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Nowadays, there are more and more variable speed drive systems in small-scale and large-scale applications such as the electric vehicle industry, household appliances, medical equipment, and other industrial fields led to the development of BLDC (Brushless DC) motors. BLDC drive has many advantages, such as higher efficiency, better speed torque characteristics, high power density, and low maintenance cost compared to other conventional motors. Most BLDC motors use a proportional-integral (PI) controller and a pulse width modulation (PWM) scheme for speed control. This article describes the simulation model of BLDC motor drive control with the help of MATLAB - SIMULINK simulation software. The built simulation model includes a BLDC motor dynamic block, Hall sensor signal generation block, inverter converter block, and PI controller.

Keywords: brushless DC motor, BLDC, six-step inverter, PI speed

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Authors: Mauricio E. Cruz, Ilse Cervantes, Manuel J. Fabela

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The evaluation of the maneuverability of road vehicles is generally carried out through the use of specialized computer programs due to the advantages they offer compared to the experimental method. These programs are based on purely geometric considerations of the characteristics of the vehicles, such as main dimensions, the location of the axles, and points of articulation, without considering parameters such as weight distribution and magnitude, tire properties, etc. In this paper, we address the problem of maneuverability in a semi-trailer truck to navigate urban streets, maneuvering yards, and parking lots, using the Ackerman principle to propose a kinematic model that, through geometric considerations, it is possible to determine the space necessary to maneuver safely. The model was experimentally validated by conducting maneuverability tests with an articulated vehicle. The measurements were made through a GPS that allows us to know the position, trajectory, and speed of the vehicle, an inertial motion unit (IMU) that allows measuring the accelerations and angular speeds in the semi-trailer, and an instrumented steering wheel that allows measuring the angle of rotation of the flywheel, the angular velocity and the torque applied to the flywheel. To obtain the steering angle of the tires, a parameterization of the complete travel of the steering wheel and its equivalent in the tires was carried out. For the tests, 3 different angles were selected, and 3 turns were made for each angle in both directions of rotation (left and right turn). The results showed that the proposed kinematic model achieved 95% accuracy for speeds below 5 km / h. The experiments revealed that that tighter maneuvers increased significantly the space required and that the vehicle maneuverability was limited by the size of the semi-trailer. The maneuverability was also tested as a function of the vehicle load and 3 different load levels we used: light, medium, and heavy. It was found that the internal turning radii also increased with the load, probably due to the changes in the tires' adhesion to the pavement since heavier loads had larger contact wheel-road surfaces. The load was found as an important factor affecting the precision of the model (up to 30%), and therefore I should be considered. The model obtained is expected to be used to improve maneuverability through a robust control system.

Keywords: articuled vehicle, experimental validation, kinematic model, maneuverability, semi-trailer truck

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Aby Nesan Raj, Sumil K. Raj, Sumesh Jayan

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The objective of the study is to formulate a self-regulation model that shall enhance the usage of Intelligent Transportation Systems by understanding the theory of self-efficacy. The core logic of the self-regulation model shall monitor driver's behavior based on the situations related to the various sources of Self Efficacy like enactive mastery, vicarious experience, verbal persuasion and physiological arousal in addition to the vehicle data. For this study, four different vehicle data, speed, drowsiness, diagnostic data and surround camera views are considered. This data shall be given to the self-regulation model for evaluation. The oddness, which is the output of self-regulation model, shall feed to Intelligent Transportation Systems where appropriate actions are being taken. These actions include warning to the user as well as the input to the related transportation systems. It is also observed that the usage of vehicle as a sensor reduces the wastage of resource utilization or duplication. Altogether, this approach enhances the intelligence of the transportation systems especially in safety, productivity and environmental performance.

Keywords: emergency management, intelligent transportation system, self-efficacy, traffic management

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Authors: Saud Hassan

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This paper shows simulation for the prediction of the flow around the backlight angle of the passenger vehicle. The CFD simulations are carried out on different car models. The Ahmed model “bluff body” used as the stander model to study aerodynamics of the backlight angle. This paper described the airflow over the different car models with different backlight angles and also on the Ahmed model to determine the trailing vortices with the varying backlight angle of a passenger vehicle body. The CFD simulation is carried out with the Ahmed body which has simplified car model mainly used in automotive industry to investigate the flow over the car body surface. The main goal of the simulation is to study the behavior of trailing vortices of these models. In this paper the air flow over the slant angle of 0,5o, 12.5o, 20o, 30o, 40o are considered. As investigating on the rear backlight angle two dimensional flows occurred at the rear slant, on the other hand when the slant angle is 30o the flow become three dimensional. Above this angle sudden drop occurred in drag.

Keywords: aerodynamics, Ahemd vehicle , backlight angle, finite element method

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Authors: G. Sirbiladze, B. Ghvaberidze, B. Matsaberidze

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A fuzzy vehicle routing problem is considered in the possibilistic environment. A new criterion, maximization of expectation of reliability for movement on closed routes is constructed. The objective of the research is to implement a two-stage scheme for solution of this problem. Based on the algorithm of preferences on the first stage, the sample of so-called “promising” routes will be selected. On the second stage, for the selected promising routes new bi-criteria problem will be solved - minimization of total traveled distance and maximization of reliability of routes. The problem will be stated as a fuzzy-partitioning problem. Two possible solutions of this scheme are considered.

Keywords: vehicle routing problem, fuzzy partitioning problem, multiple-criteria optimization, possibility theory

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Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

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Authors: Sultan Muhammed Fatih Apaydin

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In this study, two types of robot were examined as being pioneer robot and follower robot for improving of the capabilities of tracking robots. Robots continue to tracking each other and measurement of the follow-up distance between them is very important for improvements to be applied. It was achieved that the follower robot follows the pioneer robot in line with intended goals. The tests were applied to the robots in various grounds and environments in point of performance and necessary improvements were implemented by measuring the results of these tests.

Keywords: mobile robot, remote and autonomous control, infra-red sensors, arduino

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

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This paper presents a study on the trajectory of a two stage launch vehicle. The study includes dynamic responses of motion parameters as well as the variation of angles affecting the orientation of the launch vehicle (LV). LV dynamic characteristics including state vector variation with corresponding altitude and velocity for the different LV stages separation, as well as the angle of attack and flight path angles are also discussed. A flight trajectory study for the drop zone of first stage and the jettisoning of fairing are introduced in the mathematical modeling to study their effect. To increase the accuracy of the LV model, atmospheric model is used taking into consideration geographical location and the values of solar flux related to the date and time of launch, accurate atmospheric model leads to enhancement of the calculation of Mach number, which affects the drag force over the LV. The mathematical model is implemented on MATLAB based software (Simulink). The real available experimental data are compared with results obtained from the theoretical computation model. The comparison shows good agreement, which proves the validity of the developed simulation model; the maximum error noticed was generally less than 10%, which is a result that can lead to future works and enhancement to decrease this level of error.

Keywords: launch vehicle modeling, launch vehicle trajectory, mathematical modeling, Matlab- Simulink

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Wang Qian, Bian Cheng Xiang

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In recent years, with the improvement of China's urbanization level, the number of urban motor vehicles has grown rapidly. As residents' daily commuting necessities, cars cause a lot of exhaust emissions and urban traffic congestion. In the "Fourteenth Five Year Plan" of China, it is proposed to strive to reach the peak of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Urban transport accounts for a high proportion of carbon emission sources. It is an important driving force for the realization of China's carbon peak strategy. Some cities have introduced and implemented the policy of "car restriction" to solve related urban problems by reducing the use of cars. This paper analyzes the implementation of the "automobile restriction" policy, evaluates the relevant effects of the automobile restriction policy, and discusses how to better optimize the "automobile restriction" policy in the process of urban governance.

Keywords: carbon emission, traffic jams, vehicle restrictions, evaluate

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Luiz F. J. Maia

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This paper presents an approach to fuzzy control, with the use of new pertinence functions, applied in the case of an inverted pendulum. Appropriate definitions of pertinence functions to fuzzy sets make possible the implementation of the controller with only one control rule, resulting in a smooth control surface. The fuzzy control system can be implemented with analog devices, affording a true real-time performance.

Keywords: control surface, fuzzy control, Inverted pendulum, pertinence functions

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Authors: Adil Loya, Ali Haider, Arslan A. Ghaffor, Abubaker Siddique

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Simulation and modelling of Unmanned Aero Vehicle (UAV) has gained wide popularity in front of aerospace community. The demand of designing and modelling optimized control system for UAV has increased ten folds since last decade. The reason is next generation warfare is dependent on unmanned technologies. Therefore, this research focuses on the simulation of nonlinear UAV dynamics on Simulink and its integration with Flightgear. There has been lots of research on implementation of optimizing control using Simulink, however, there are fewer known techniques to simulate these dynamics over Flightgear and a tedious technique of acquiring data has been tackled in this research horizon. Sending data to Flightgear is easy but receiving it from Simulink is not that straight forward, i.e. we can only receive control data on the output. However, in this research we have managed to get the data out from the Flightgear by implementation of level 2 s-function block within Simulink. Moreover, the results captured from Flightgear over a Universal Datagram Protocol (UDP) communication are then compared with the attitude signal that were sent previously. This provide useful information regarding the difference in outputs attained from Simulink to Flightgear. It was found that values received on Simulink were in high agreement with that of the Flightgear output. And complete study has been conducted in a discrete way.

Keywords: aerospace, flight control, flightgear, communication, Simulink

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Authors: Prakash M.N, Mahesh G, Muhammed Rafi K.M, Shiju P. Nair

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Introduction: In launch vehicle missions, Reaction Control thrusters are being used for the three-axis stabilization of the vehicle during the coasting phases. A pressure-fed propulsion system is used for the operation of these thrusters due to its less complexity. In liquid stages, these thrusters are designed to draw propellant from the same tank used for the main propulsion system. So in order to regulate the propellant flow rates of these thrusters, flow control orifices are used in feed lines. These orifices are calibrated separately as per the flow rate requirement of individual thrusters for the nominal operating conditions. In some missions, it was observed that the thrusters were operated at higher thrust than nominal. This point was addressed through a series of cold flow and hot tests carried out in-ground and this paper elaborates the details of the same. Discussion: In order to find out the exact reason for this phenomenon, two flight configuration thrusters were identified and hot tested in the ground with calibrated orifices and feed lines. During these tests, the chamber pressure, which is directly proportional to the thrust, is measured. In both cases, chamber pressures higher than the nominal by 0.32bar to 0.7bar were recorded. The increase in chamber pressure is due to an increase in the oxidizer flow rate of both the thrusters. Upon further investigation, it is observed that the calibration of the feed line is done with ambient pressure downstream. But in actual flight conditions, the orifices will be subjected to operate with 10 to 11bar pressure downstream. Due to this higher downstream pressure, the flow through the orifices increases and thereby, the thrusters operate with higher chamber pressure values. Conclusion: As part of further investigatory tests, two numbers of fresh thrusters were realized. Orifice tuning of these thrusters was carried out in three different ways. In the first trial, the orifice tuning was done by simulating 1bar pressure downstream. The second trial was done with the injector assembled downstream. In the third trial, the downstream pressure equal to the flight injection pressure was simulated downstream. Using these calibrated orifices, hot tests were carried out in simulated vacuum conditions. Chamber pressure and flow rate values were exactly matching with the prediction for the second and third trials. But for the first trial, the chamber pressure values obtained in the hot test were more than the prediction. This clearly shows that the flow is detached in the 1st trial and attached for the 2nd & 3rd trials. Hence, the error in tuning the flow control orifices is pinpointed as the reason for this higher chamber pressure observed in flight.

Keywords: reaction control thruster, propellent, orifice, chamber pressure

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Authors: Yue Huang, Yiheng Feng

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Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

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Authors: Ilgoun Kim, Jongpil Jeong

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Recently, a connected industrial parks (CIPs) architecture using new technologies such as RFID, cloud computing, CPS, Big Data, 5G 5G, IIOT, VR-AR, and ventral AI algorithms based on IoT has been proposed. This researcher noted the vehicle junction problem (VJP) as a more specific detail of the CIPs architectural models. The VJP noted by this researcher includes 'efficient AI physical connection challenges for vehicles' through ventilation, 'financial and financial issues with complex vehicle physical connections,' and 'welfare and working conditions of the performing personnel involved in complex vehicle physical connections.' In this paper, we propose a public solution architecture for the 'electronic financial problem of complex vehicle physical connections' as a detailed task during the vehicle junction problem (VJP). The researcher sought solutions to businesses, consumers, and Korean social problems through technological advancement. We studied how the beneficiaries of technological development can benefit from technological development with many consumers in Korean society and many small and small Korean company managers, not some specific companies. In order to more specifically implement the connected industrial parks (CIPs) architecture using the new technology, we noted the vehicle junction problem (VJP) within the smart factory industrial complex and noted the process of achieving the vehicle junction problem performance among several electronic processes. This researcher proposes a more detailed, integrated public finance enterprise architecture among the overall CIPs architectures. The main details of the public integrated financial enterprise architecture were largely organized into four main categories: 'business', 'data', 'technique', and 'finance'.

Keywords: enterprise architecture, IT Finance, smart logistics, CIPs

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

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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

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Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang

Abstract:

This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.

Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

Abstract:

Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: driver, fuzzy logic, perception reaction time, premise variable

Procedia PDF Downloads 277

Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

Abstract:

The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

Procedia PDF Downloads 178