Mixed traffic systems are dynamically complex since there are many parameters and variables that influence the interactions between the different kinds of vehicles. Modeling the behavior of vehicles, especially motorcycle which has erratic behavior is still being developed continuously, especially in developing countries which have heterogeneous traffic. To get a better understanding of motorcycle behavior, one can look at maneuvers performed by drivers. In this research, we tried to build a model of motorcycle movement which only focused on maneuver action to avoid the obstacle along with the trajectories using a Markov Chain approach. In Markov Chain, the maneuver of motorcycle will described by state transition. The state transition model is depend on probability function which will use for determine what action will be executed next. The maneuver of motorcycle using Markov Chain model was validated by comparing the analytical result with the naturalistic data, with similarity is calculated using MSE. In order to know how good our proposed method can describe the maneuver of motorcycle, we try to compare the MSE of the trajectory based on Markov Chain model with those using polynomial approach. The MSE results showed the performance of Markov Chain Model give the smallest MSE which 0.7666 about 0.24 better than 4 order polynomial.
Modeling of driver lane choice behavior with artificial neural networks (ann)...cseij
In parallel to the economic developments, the importance of road transportation was significantly
increased in Turkey. As a result of this, long-distance freight transportation gains more importance and
hence numbers of the heavy vehicles were significantly increased. Consequently, road surface deformations
are observed on the roads as the increasing freight transportation and climatic conditions influence the
road surface. Therefore, loss of functionality of the road surface is observed and drivers are much prone to
accident due to their driving characteristics as they can have more tendencies to change their lanes not to
pass through the deformation area. In this study, the lane changing behaviors of the drivers were
investigated and both Artificial Neural Network (ANN) and Linear Regression (LR) models were proposed
to simulate the driver behavior of lane changing who approach to a specific road deformation area. The
potential of ANN model for simulating the driver behavior was evaluated with successive comparison of the
model performances with LR model. While there was a slight performance increase for the ANN model with
respect to LR model, it is quite evident that, ANN models can play an important role for predicting the
driver behavior approaching a road surface deformation. It can be said that, approaching speed plays an
important factor on the lane changing behavior of a driver. This can be criticized by the fact that, drivers
with high approaching speeds more likely pass through the deformation to avoid the accidents while
changing their lanes with a high speed.
Traffic State Estimation and Prediction under Heterogeneous Traffic ConditionsIDES Editor
The recent economic growth in developing countries
like India has resulted in an intense increase of vehicle
ownership and use, as witnessed by severe traffic congestion
and bottlenecks during peak hours in most of the metropolitan
cities. Intelligent Transportation Systems (ITS) aim to reduce
traffic congestion by adopting various strategies such as
providing pre-trip and en-route traffic information thereby
reducing demand, adaptive signal control for area wide
optimization of traffic flow, etc. The successful deployment
and the reliability of these systems largely depend on the
accurate estimation of the current traffic state and quick and
reliable prediction to future time steps. At a macroscopic level,
this involves the prediction of fundamental traffic stream
parameters which include speed, density and flow in spacetime
domain. The complexity of prediction is enhanced by
heterogeneous traffic conditions as prevailing in India due to
less lane discipline and complex interactions among different
vehicle types. Also, there is no exclusive traffic flow model for
heterogeneous traffic conditions which can characterize the
traffic stream at a macroscopic level. Hence, the present study
tries to explore the applicability of an existing macroscopic
model, namely the Lighthill-Whitham-Richards (LWR) model,
for short term prediction of traffic flow in a busy arterial in
the city of Chennai, India, under heterogeneous traffic
conditions. Both linear and exponential speed-density
relations were considered and incorporated into the
macroscopic model. The resulting partial differential
equations are solved numerically and the results are found to
be encouraging. This model can ultimately be helpful for the
implementation of ATIS/ATMS applications under
heterogeneous traffic environment.
Kineto-Elasto Dynamic Analysis of Robot Manipulator Puma-560IOSR Journals
Current industrial robots are made very heavy to achieve high Stiffness
which increases the accuracy of their motion. However this heaviness limits the robot speed and in masses the
required energy to move the system. The requirement for higher speed and better system performance makes it
necessary to consider a new generation of light weight manipulators as an alternative to today's massive
inefficient ones. Light weight manipulators require Less energy to move and they have larger payload abilities
and more maneuverability. However due to the dynamic effects of structural flexibility, their control is much
more difficult. Therefore, there is a need to develop accurate dynamic models for design and control of such
systems.This project presents the flexibility and Kineto - Elasto dynamic analysis of robot manipulator
considering deflection. Based on the distributed parameter method, the generalized motion equations of robot
manipulator with flexible links are derived. The final formulation of the motion equations is used to model
general complex elastic manipulators with nonlinear rigid-body and elastic motion in dynamics and it can be
used in the flexibility analysis of robot manipulators and spatial mechanisms. Manipulator end-effector path
trajectory, velocity and accelerations are plotted. Joint torques is to be determined for each joint trajectory
(Dynamics) .Using joint torques, static loading due to link’s masses, masses at joints, and payload, the robot
arms elastic deformations are to be found by using ANSYS-12.0 software package. Elastic compensation is
inserted in coordinates of robotic programming to get exact end-effectors path. A comparison of paths
trajectory of the end-effector is to be plotted. Also variation of torques is plotted after considering elastic
compensation. These torque variations are included in the robotic programming for getting the accurate endeffect
or’s path trajectory
Fuzzy Logic Model for Traffic CongestionIOSR Journals
Abstract: Traffic congestion has become a serious problem in the urban districts. This is mainly due to the
rapid increase in the number and the use of vehicles. Travel time, travel safety, environmental quality, and life
quality are all adversely affected by traffic congestion. Many traffic control systems have been developed and
installed to alleviate the problem with limited success. Traffic demands are still high and increasing. The main
focus of this report is to introduce a versatile fuzzy logic traffic flow model capable of making optimal traffic
predictions. This model can be used to evaluate various traffic-light timing plans. More importantly, it provides
a framework for implementing adaptive traffic signal controllers based on fuzzy logic technology. When
implemented it solved the problem of waiting time, travel cost, accident, traffic congestion.
Key words: Traffic Congestion, fuzzy logic, Traffic Density, fuzzy controller, conventional controller.
Modeling of driver lane choice behavior with artificial neural networks (ann)...cseij
In parallel to the economic developments, the importance of road transportation was significantly
increased in Turkey. As a result of this, long-distance freight transportation gains more importance and
hence numbers of the heavy vehicles were significantly increased. Consequently, road surface deformations
are observed on the roads as the increasing freight transportation and climatic conditions influence the
road surface. Therefore, loss of functionality of the road surface is observed and drivers are much prone to
accident due to their driving characteristics as they can have more tendencies to change their lanes not to
pass through the deformation area. In this study, the lane changing behaviors of the drivers were
investigated and both Artificial Neural Network (ANN) and Linear Regression (LR) models were proposed
to simulate the driver behavior of lane changing who approach to a specific road deformation area. The
potential of ANN model for simulating the driver behavior was evaluated with successive comparison of the
model performances with LR model. While there was a slight performance increase for the ANN model with
respect to LR model, it is quite evident that, ANN models can play an important role for predicting the
driver behavior approaching a road surface deformation. It can be said that, approaching speed plays an
important factor on the lane changing behavior of a driver. This can be criticized by the fact that, drivers
with high approaching speeds more likely pass through the deformation to avoid the accidents while
changing their lanes with a high speed.
Traffic State Estimation and Prediction under Heterogeneous Traffic ConditionsIDES Editor
The recent economic growth in developing countries
like India has resulted in an intense increase of vehicle
ownership and use, as witnessed by severe traffic congestion
and bottlenecks during peak hours in most of the metropolitan
cities. Intelligent Transportation Systems (ITS) aim to reduce
traffic congestion by adopting various strategies such as
providing pre-trip and en-route traffic information thereby
reducing demand, adaptive signal control for area wide
optimization of traffic flow, etc. The successful deployment
and the reliability of these systems largely depend on the
accurate estimation of the current traffic state and quick and
reliable prediction to future time steps. At a macroscopic level,
this involves the prediction of fundamental traffic stream
parameters which include speed, density and flow in spacetime
domain. The complexity of prediction is enhanced by
heterogeneous traffic conditions as prevailing in India due to
less lane discipline and complex interactions among different
vehicle types. Also, there is no exclusive traffic flow model for
heterogeneous traffic conditions which can characterize the
traffic stream at a macroscopic level. Hence, the present study
tries to explore the applicability of an existing macroscopic
model, namely the Lighthill-Whitham-Richards (LWR) model,
for short term prediction of traffic flow in a busy arterial in
the city of Chennai, India, under heterogeneous traffic
conditions. Both linear and exponential speed-density
relations were considered and incorporated into the
macroscopic model. The resulting partial differential
equations are solved numerically and the results are found to
be encouraging. This model can ultimately be helpful for the
implementation of ATIS/ATMS applications under
heterogeneous traffic environment.
Kineto-Elasto Dynamic Analysis of Robot Manipulator Puma-560IOSR Journals
Current industrial robots are made very heavy to achieve high Stiffness
which increases the accuracy of their motion. However this heaviness limits the robot speed and in masses the
required energy to move the system. The requirement for higher speed and better system performance makes it
necessary to consider a new generation of light weight manipulators as an alternative to today's massive
inefficient ones. Light weight manipulators require Less energy to move and they have larger payload abilities
and more maneuverability. However due to the dynamic effects of structural flexibility, their control is much
more difficult. Therefore, there is a need to develop accurate dynamic models for design and control of such
systems.This project presents the flexibility and Kineto - Elasto dynamic analysis of robot manipulator
considering deflection. Based on the distributed parameter method, the generalized motion equations of robot
manipulator with flexible links are derived. The final formulation of the motion equations is used to model
general complex elastic manipulators with nonlinear rigid-body and elastic motion in dynamics and it can be
used in the flexibility analysis of robot manipulators and spatial mechanisms. Manipulator end-effector path
trajectory, velocity and accelerations are plotted. Joint torques is to be determined for each joint trajectory
(Dynamics) .Using joint torques, static loading due to link’s masses, masses at joints, and payload, the robot
arms elastic deformations are to be found by using ANSYS-12.0 software package. Elastic compensation is
inserted in coordinates of robotic programming to get exact end-effectors path. A comparison of paths
trajectory of the end-effector is to be plotted. Also variation of torques is plotted after considering elastic
compensation. These torque variations are included in the robotic programming for getting the accurate endeffect
or’s path trajectory
Fuzzy Logic Model for Traffic CongestionIOSR Journals
Abstract: Traffic congestion has become a serious problem in the urban districts. This is mainly due to the
rapid increase in the number and the use of vehicles. Travel time, travel safety, environmental quality, and life
quality are all adversely affected by traffic congestion. Many traffic control systems have been developed and
installed to alleviate the problem with limited success. Traffic demands are still high and increasing. The main
focus of this report is to introduce a versatile fuzzy logic traffic flow model capable of making optimal traffic
predictions. This model can be used to evaluate various traffic-light timing plans. More importantly, it provides
a framework for implementing adaptive traffic signal controllers based on fuzzy logic technology. When
implemented it solved the problem of waiting time, travel cost, accident, traffic congestion.
Key words: Traffic Congestion, fuzzy logic, Traffic Density, fuzzy controller, conventional controller.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Machine learning systems based on xgBoost and MLP neural network applied in s...aciijournal
In this work, the internal impedance of the lithium-ion battery pack (important measure of the degradation level of the batteries) is estimated by means of machine learning systems based on supervised learning techniques MLP - Multi Layer Perceptron - neural network and xgBoost - Gradient Tree Boosting. Therefore, characteristics of the electric power system, in which the battery pack is inserted, are extracted and used in the construction of supervised models through the application of two different techniques based on Gradient Tree Boosting and Multi Layer Perceptron neural network. Finally, with the application of statistical validation techniques, the accuracy of both models are calculated and used for the comparison between them and the feasibility analysis regarding the use of such models in real systems.
Potential Development of Vehicle Traction Levitation Systems with Magnetic Su...IAES-IJPEDS
Below is given the brief analysis of development trend for vehicle traction levitation systems with magnetic suspension. It is presented the assessment of potential development of traction levitation systems in terms of their simplicity. The examples are considered of technical solutions focused on reducing the complexity of transport systems. It is proposed the forecast of their further development.
Study and Analysis of Design Optimization and Synthesis of Robotic ARMINFOGAIN PUBLICATION
A robot is a mechanical or virtual artificial agent, usually an electro-mechanical machine that is guided by a computer program or electronic circuitry. Robots can be autonomous or semi-autonomous. In this thesis, design optimization strategies and synthesis for robotic arm are studied. In the design process, novel optimization methods have been developed to reduce the mass of the whole robotic arm. The optimization of the robotic arm is conducted at three different levels, with the main objective to minimize the robot mass. At the first level, only the drive-train of the robotic arm is optimized. The design process of a robotic arm is decomposed into selection of components for the drive-train to reduce the weight At the second level, kinematic data is combined with the drive-train in the optimization. For this purpose, a dynamic model of the robot is required. Constraints are formulated on the motors, gearboxes and kinematic performance At the third level, a systematic optimization approach is developed, which contains design variables of structural dimensions, geometric dimensions and drive-train composes. Constraints are formulated on the stiffness and deformation. The stiffness and deformation of the arm are calculated through FEA simulation. The main objective of the thesis is to design optimization and synthesis analysis of robotic arm. The corresponding deflections, stresses and strains for that load will be find out by suing the method of finite element analysis.
Review on Design & Implementation of Road Side Symbol Detection In VANETIJERA Editor
Establishment of vehicular ad-hoc network plays important role in smart traffic management system. Researcher
can create VANET by information sharing of road side unit, vehicle and traffic system & implementing it in real
world. This system implemented to detect road signs from a moving vehicle. In this technology vehicle is able
to detect traffic signs which are on the road side boards e.g. "speed limit" or "school" or "turn ahead". Consider
a condition, user is driving a car at night or in rainy season then it is not possible for driver to keep watch on
each and every road symbol or the message plates like turn, speed breaker, school, diversion etc. Here in this
proposed system every road side board or symbol will use one signal transmitter and the moment vehicle passes
from that road side board the vehicle will receive signals with the help of receiver and indicates the symbol on
LCD display which is in the car. So that the driver can able to concentrate on driving vehicle.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Deep neural network for lateral control of self-driving cars in urban environ...IAESIJAI
The exponential growth of the automotive industry clearly indicates that self-driving cars are the future of transportation. However, their biggest challenge lies in lateral control, particularly in urban bottlenecking environments, where disturbances and obstacles are abundant. In these situations, the ego vehicle has to follow its own trajectory while rapidly correcting deviation errors without colliding with other nearby vehicles. Various research efforts have focused on developing lateral control approaches, but these methods remain limited in terms of response speed and control accuracy. This paper presents a control strategy using a deep neural network (DNN) controller to effectively keep the car on the centerline of its trajectory and adapt to disturbances arising from deviations or trajectory curvature. The controller focuses on minimizing deviation errors. The Matlab/Simulink software is used for designing and training the DNN. Finally, simulation results confirm that the suggested controller has several advantages in terms of precision, with lateral deviation remaining below 0.65 meters, and rapidity, with a response time of 0.7 seconds, compared to traditional controllers in solving lateral control.
A Review on Road Traffic Models for Intelligent Transportation System (ITS)IJSRD
Traffic flow models seek to describe the interaction of vehicles with their drivers and the infrastructure. Almost all the models directly or indirectly characterize the relationship among the traffic variables: the position, the speed, the flow, and the density of vehicles. These relationships can be based on either the behavior of individual vehicles in a traffic network in relation to the dynamics of other vehicles, the overall characteristics of the flow of vehicles in a traffic network, or a combination of the behavior of individual vehicles in a traffic network and the overall traffic flow characteristics. This paper describes the different models for automatic Traffic control system.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATI...cscpconf
The intensive development of traffic engineering and technologies that are integrated into vehicles, roads and their surroundings, bring opportunities of real time transport mobility modeling. Based on such model it is then possible to establish a predictive layer that is capable of predicting short and long term traffic flow behavior. It is possible to create the real time model of traffic mobility based on generated data. However, data may have different geographical, temporal or other constraints, or failures. It is therefore appropriate to develop tools that artificially create missing data, which can then be assimilated with real data. This paper presents a mechanism describing strategies of generating artificial data using microsimulations. It describes traffic microsimulation based on our solution of multiagent framework over which a system for generating traffic data is built. The system generates data of a structure corresponding to the data acquired in the real world.
IMPORTANCE OF REALISTIC MOBILITY MODELS FOR VANET NETWORK SIMULATIONIJCNCJournal
In the performance evaluation of a protocol for a vehicular ad hoc network, the protocol should be tested under a realistic conditions including, representative data traffic models, and realistic movements of the mobile nodes which are the vehicles (i.e., a mobility model). This work is a comparative study between two mobility models that are used in the simulations of vehicular networks, i.e., MOVE (MObility model generator for VEhicular networks) and CityMob, a mobility pattern generator for VANET. We describe several mobility models for VANET simulations.
In this paper we aim to show that the mobility models can significantly affect the simulation results in VANET networks. The results presented in this article prove the importance of choosing a suitable real world scenario for performances studies of routing protocols in this kind of network.
Adaptive traffic lights based on traffic flow prediction using machine learni...IJECEIAES
Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbor regressor to predict traffic flow and reduce traffic congestion at intersections. We used the public roads dataset from the UK national road traffic to test our models. All machine learning algorithms obtained good performance metrics, indicating that they are valid for implementation in smart traffic light systems. Next, we implemented an adaptive traffic light system based on a random forest regressor model, which adjusts the timing of green and red lights depending on the road width, traffic density, types of vehicles, and expected traffic. Simulations of the proposed system show a 30.8% reduction in traffic congestion, thus justifying its effectiveness and the interest of deploying it to regulate the signaling problem in intersections.
A Framework for Traffic Planning and Forecasting using Micro-Simulation Calib...ITIIIndustries
This paper presents the application of microsimulation for traffic planning and forecasting, and proposes a new framework to model complex traffic conditions by calibrating and adjusting traffic parameters of a microsimulation model. By using an open source micro-simulator package, TRANSIMS, in this study, animated and numerical results were produced and analysed. The framework of traffic model calibration was evaluated for its usefulness and practicality. Finally, we discuss future applications such as providing end users with real time traffic information through Intelligent Transport System (ITS) integration.
Car-Following Parameters by Means of Cellular Automata in the Case of EvacuationCSCJournals
This study is attention to the car-following model, an important part in the micro traffic flow. Different from Nagel–Schreckenberg’s studies in which car-following model without agent drivers and diligent ones, agent drivers and diligent ones are proposed in the car-following part in this work and lane-changing is also presented in the model. The impact of agent drivers and diligent ones under certain circumstances such as in the case of evacuation is considered. Based on simulation results, the relations between evacuation time and diligent drivers are obtained by using different amounts of agent drivers; comparison between previous (Nagel–Schreckenberg) and proposed model is also found in order to find the evacuation time. Besides, the effectiveness of reduction the evacuation time is presented for various agent drivers and diligent ones.
CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATI...csandit
The intensive development of traffic engineering and technologies that are integrated into
vehicles, roads and their surroundings, bring opportunities of real time transport mobility
modeling. Based on such model it is then possible to establish a predictive layer that is capable
of predicting short and long term traffic flow behavior. It is possible to create the real time
model of traffic mobility based on generated data. However, data may have different
geographical, temporal or other constraints, or failures. It is therefore appropriate to develop
tools that artificially create missing data, which can then be assimilated with real data. This
paper presents a mechanism describing strategies of generating artificial data using
microsimulations. It describes traffic microsimulation based on our solution of multiagent
framework over which a system for generating traffic data is built. The system generates data of
a structure corresponding to the data acquired in the real world.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Machine learning systems based on xgBoost and MLP neural network applied in s...aciijournal
In this work, the internal impedance of the lithium-ion battery pack (important measure of the degradation level of the batteries) is estimated by means of machine learning systems based on supervised learning techniques MLP - Multi Layer Perceptron - neural network and xgBoost - Gradient Tree Boosting. Therefore, characteristics of the electric power system, in which the battery pack is inserted, are extracted and used in the construction of supervised models through the application of two different techniques based on Gradient Tree Boosting and Multi Layer Perceptron neural network. Finally, with the application of statistical validation techniques, the accuracy of both models are calculated and used for the comparison between them and the feasibility analysis regarding the use of such models in real systems.
Potential Development of Vehicle Traction Levitation Systems with Magnetic Su...IAES-IJPEDS
Below is given the brief analysis of development trend for vehicle traction levitation systems with magnetic suspension. It is presented the assessment of potential development of traction levitation systems in terms of their simplicity. The examples are considered of technical solutions focused on reducing the complexity of transport systems. It is proposed the forecast of their further development.
Study and Analysis of Design Optimization and Synthesis of Robotic ARMINFOGAIN PUBLICATION
A robot is a mechanical or virtual artificial agent, usually an electro-mechanical machine that is guided by a computer program or electronic circuitry. Robots can be autonomous or semi-autonomous. In this thesis, design optimization strategies and synthesis for robotic arm are studied. In the design process, novel optimization methods have been developed to reduce the mass of the whole robotic arm. The optimization of the robotic arm is conducted at three different levels, with the main objective to minimize the robot mass. At the first level, only the drive-train of the robotic arm is optimized. The design process of a robotic arm is decomposed into selection of components for the drive-train to reduce the weight At the second level, kinematic data is combined with the drive-train in the optimization. For this purpose, a dynamic model of the robot is required. Constraints are formulated on the motors, gearboxes and kinematic performance At the third level, a systematic optimization approach is developed, which contains design variables of structural dimensions, geometric dimensions and drive-train composes. Constraints are formulated on the stiffness and deformation. The stiffness and deformation of the arm are calculated through FEA simulation. The main objective of the thesis is to design optimization and synthesis analysis of robotic arm. The corresponding deflections, stresses and strains for that load will be find out by suing the method of finite element analysis.
Review on Design & Implementation of Road Side Symbol Detection In VANETIJERA Editor
Establishment of vehicular ad-hoc network plays important role in smart traffic management system. Researcher
can create VANET by information sharing of road side unit, vehicle and traffic system & implementing it in real
world. This system implemented to detect road signs from a moving vehicle. In this technology vehicle is able
to detect traffic signs which are on the road side boards e.g. "speed limit" or "school" or "turn ahead". Consider
a condition, user is driving a car at night or in rainy season then it is not possible for driver to keep watch on
each and every road symbol or the message plates like turn, speed breaker, school, diversion etc. Here in this
proposed system every road side board or symbol will use one signal transmitter and the moment vehicle passes
from that road side board the vehicle will receive signals with the help of receiver and indicates the symbol on
LCD display which is in the car. So that the driver can able to concentrate on driving vehicle.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Deep neural network for lateral control of self-driving cars in urban environ...IAESIJAI
The exponential growth of the automotive industry clearly indicates that self-driving cars are the future of transportation. However, their biggest challenge lies in lateral control, particularly in urban bottlenecking environments, where disturbances and obstacles are abundant. In these situations, the ego vehicle has to follow its own trajectory while rapidly correcting deviation errors without colliding with other nearby vehicles. Various research efforts have focused on developing lateral control approaches, but these methods remain limited in terms of response speed and control accuracy. This paper presents a control strategy using a deep neural network (DNN) controller to effectively keep the car on the centerline of its trajectory and adapt to disturbances arising from deviations or trajectory curvature. The controller focuses on minimizing deviation errors. The Matlab/Simulink software is used for designing and training the DNN. Finally, simulation results confirm that the suggested controller has several advantages in terms of precision, with lateral deviation remaining below 0.65 meters, and rapidity, with a response time of 0.7 seconds, compared to traditional controllers in solving lateral control.
A Review on Road Traffic Models for Intelligent Transportation System (ITS)IJSRD
Traffic flow models seek to describe the interaction of vehicles with their drivers and the infrastructure. Almost all the models directly or indirectly characterize the relationship among the traffic variables: the position, the speed, the flow, and the density of vehicles. These relationships can be based on either the behavior of individual vehicles in a traffic network in relation to the dynamics of other vehicles, the overall characteristics of the flow of vehicles in a traffic network, or a combination of the behavior of individual vehicles in a traffic network and the overall traffic flow characteristics. This paper describes the different models for automatic Traffic control system.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATI...cscpconf
The intensive development of traffic engineering and technologies that are integrated into vehicles, roads and their surroundings, bring opportunities of real time transport mobility modeling. Based on such model it is then possible to establish a predictive layer that is capable of predicting short and long term traffic flow behavior. It is possible to create the real time model of traffic mobility based on generated data. However, data may have different geographical, temporal or other constraints, or failures. It is therefore appropriate to develop tools that artificially create missing data, which can then be assimilated with real data. This paper presents a mechanism describing strategies of generating artificial data using microsimulations. It describes traffic microsimulation based on our solution of multiagent framework over which a system for generating traffic data is built. The system generates data of a structure corresponding to the data acquired in the real world.
IMPORTANCE OF REALISTIC MOBILITY MODELS FOR VANET NETWORK SIMULATIONIJCNCJournal
In the performance evaluation of a protocol for a vehicular ad hoc network, the protocol should be tested under a realistic conditions including, representative data traffic models, and realistic movements of the mobile nodes which are the vehicles (i.e., a mobility model). This work is a comparative study between two mobility models that are used in the simulations of vehicular networks, i.e., MOVE (MObility model generator for VEhicular networks) and CityMob, a mobility pattern generator for VANET. We describe several mobility models for VANET simulations.
In this paper we aim to show that the mobility models can significantly affect the simulation results in VANET networks. The results presented in this article prove the importance of choosing a suitable real world scenario for performances studies of routing protocols in this kind of network.
Adaptive traffic lights based on traffic flow prediction using machine learni...IJECEIAES
Traffic congestion prediction is one of the essential components of intelligent transport systems (ITS). This is due to the rapid growth of population and, consequently, the high number of vehicles in cities. Nowadays, the problem of traffic congestion attracts more and more attention from researchers in the field of ITS. Traffic congestion can be predicted in advance by analyzing traffic flow data. In this article, we used machine learning algorithms such as linear regression, random forest regressor, decision tree regressor, gradient boosting regressor, and K-neighbor regressor to predict traffic flow and reduce traffic congestion at intersections. We used the public roads dataset from the UK national road traffic to test our models. All machine learning algorithms obtained good performance metrics, indicating that they are valid for implementation in smart traffic light systems. Next, we implemented an adaptive traffic light system based on a random forest regressor model, which adjusts the timing of green and red lights depending on the road width, traffic density, types of vehicles, and expected traffic. Simulations of the proposed system show a 30.8% reduction in traffic congestion, thus justifying its effectiveness and the interest of deploying it to regulate the signaling problem in intersections.
A Framework for Traffic Planning and Forecasting using Micro-Simulation Calib...ITIIIndustries
This paper presents the application of microsimulation for traffic planning and forecasting, and proposes a new framework to model complex traffic conditions by calibrating and adjusting traffic parameters of a microsimulation model. By using an open source micro-simulator package, TRANSIMS, in this study, animated and numerical results were produced and analysed. The framework of traffic model calibration was evaluated for its usefulness and practicality. Finally, we discuss future applications such as providing end users with real time traffic information through Intelligent Transport System (ITS) integration.
Car-Following Parameters by Means of Cellular Automata in the Case of EvacuationCSCJournals
This study is attention to the car-following model, an important part in the micro traffic flow. Different from Nagel–Schreckenberg’s studies in which car-following model without agent drivers and diligent ones, agent drivers and diligent ones are proposed in the car-following part in this work and lane-changing is also presented in the model. The impact of agent drivers and diligent ones under certain circumstances such as in the case of evacuation is considered. Based on simulation results, the relations between evacuation time and diligent drivers are obtained by using different amounts of agent drivers; comparison between previous (Nagel–Schreckenberg) and proposed model is also found in order to find the evacuation time. Besides, the effectiveness of reduction the evacuation time is presented for various agent drivers and diligent ones.
CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATI...csandit
The intensive development of traffic engineering and technologies that are integrated into
vehicles, roads and their surroundings, bring opportunities of real time transport mobility
modeling. Based on such model it is then possible to establish a predictive layer that is capable
of predicting short and long term traffic flow behavior. It is possible to create the real time
model of traffic mobility based on generated data. However, data may have different
geographical, temporal or other constraints, or failures. It is therefore appropriate to develop
tools that artificially create missing data, which can then be assimilated with real data. This
paper presents a mechanism describing strategies of generating artificial data using
microsimulations. It describes traffic microsimulation based on our solution of multiagent
framework over which a system for generating traffic data is built. The system generates data of
a structure corresponding to the data acquired in the real world.
Evolutionary reinforcement learning multi-agents system for intelligent traf...IJECEIAES
Due to the rapid growth of urban vehicles, traffic congestion has become more serious. The signalized intersections are used all over the world and still established in the new construction. This paper proposes a self-adapted approach, called evolutionary reinforcement learning multi-agents system (ERL-MA), which combines computational intelligence and machine learning. The concept of this work is to build an intelligent agent capable of developing senior skills to manage the traffic light control system at any type of junction, using two powerful tools: learning from the confronted experience and the assumption using the randomization concept. The ERL-MA is an independent multi-agents system composed of two layers: the modeling and the decision layers. The modeling layer uses the intersection modeling using generalized fuzzy graph technique. The decision layer uses two methods: the novel greedy genetic algorithm (NGGA), and the Q-learning. In the Q-learning method, a multi Q-tables strategy and a new reward formula are proposed. The experiments used in this work relied on a real case of study with a simulation of one-hour scenario at Pasubio area in Italy. The obtained results show that the ERL-MA system succeeds to achieve competitive results comparing to urban traffic optimization by integrated automation (UTOPIA) system using different metrics.
Ever increasing number of vehicles on road imposes a due concern about road safety on the automobile manufacturers and the users as well. Cargo vehicle is a major part of automobile sector and attained a new look in the era of internet of things. The current paper pr esents various modern trends being incorporated in Cargo vehicles to monitor different vehicles and environmental par ameters to ensure road safety. Authors have extended the scope of study with due c onsideration to R&D efforts in advanced sensing,environmental perception and interactive driver ass istance systems to avoid road accidents due to une ven/over loading of cargo vehicles in specific. With this ki nd of challenging efforts,the authors aim to conve rge important technologies such as automotive-electronics,sensor s and mobile communication towards safe operation o f cargo vehicles while negotiating the road.
Path tracking control of differential drive mobile robot based on chaotic-bi...IJECEIAES
Mobile robots are typically depending only on robot kinematics control. However, when high-speed motions and highly loaded transfer are considered, it is necessary to analyze dynamics of the robot to limit tracking error. The goal of this paper is to present a new algorithm, chaotic-billiards optimizer (C-BO) to optimize internal controller parameters of a differentialdrive mobile robot (DDMR)-based dynamic model. The C-BO algorithm is notable for its ease of implementation, minimal number of design parameters, high convergence speed, and low computing burden. In addition, a comparison between the performance of C-BO and ant colony optimization (ACO) to determine the optimum controller coefficient that provides superior performance and convergence of the path tracking. The ISE criterion is selected as a fitness function in a simulation-based optimization strategy. For the point of accuracy, the velocity-based dynamic compensation controller was successfully integrated with the motion controller proposed in this study for the robot's kinematics. Control structure of the model was tested using MATLAB/Simulink. The results demonstrate that the suggested C-BO, with steady state error performance of 0.6 percent compared to ACO's 0.8 percent, is the optimum alternative for parameter optimizing the controller for precise path tracking. Also, it offers advantages of quick response, high tracking precision, and outstanding anti-interference capability
Similar to Motorcycle Movement Model Based on Markov Chain Process in Mixed Traffic (20)
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Fuzzy logic method-based stress detector with blood pressure and body tempera...IJECEIAES
In this study, using the fuzzy logic method, a stress detection tool was created with body temperature and blood pressure parameters as indicators to determine a person's stress level. This tool uses the LM35DZ sensor to detect body temperature, the MPX5100GP sensor to read blood pressure values, and Arduino Uno as a data processor from sensor readings which are then calculated using the fuzzy logic method as a stress level decisionmaker. The resulting output measures blood pressure, body temperature, and the stress level experienced by a person, which will be displayed on the liquid crystal display. Based on the results of testing the body temperature parameter, the highest error generated was 1.17%, and for the blood pressure parameter, the highest error was 2.5% for systole and 0.93% for diastole. Furthermore, testing the stress level displayed on the tool is compared to the depression, anxiety, and stress scales 42 (DASS 42), a psychological stress measuring instrument. From the results of testing the tool with the questionnaire, the average conformity level is 74%.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
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Motorcycle Movement Model Based on Markov Chain Process in Mixed Traffic
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 8, No. 5, October 2018, pp. 3149 – 3157
ISSN: 2088-8708 3149
Institute of Advanced Engineering and Science
w w w . i a e s j o u r n a l . c o m
Motorcycle Movement Model Based on Markov Chain
Process in Mixed Traffic
Rina Mardiati1
, Bambang R. Trilaksono2
, Yudi S. Gondokaryono3
, and Sony S. Wibowo4
1,2,3
School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
4
Department of Civil Engineering, Bandung Institute of Technology, Indonesia
Article Info
Article history:
Received August 9, 2017
Revised June 25, 2018
Accepted July 7, 2018
Keyword:
Markov Chain
Maneuver Intention
Vehicle Movement
Mixed Traffic
ABSTRACT
Mixed traffic systems are dynamically complex since there are many parameters and
variables that influence the interactions between the different kinds of vehicles. Mod-
eling the behavior of vehicles, especially motorcycle which has erratic behavior is still
being developed continuously, especially in developing countries which have hetero-
geneous traffic. To get a better understanding of motorcycle behavior, one can look at
maneuvers performed by drivers. In this research, we tried to build a model of motor-
cycle movement which only focused on maneuver action to avoid the obstacle along
with the trajectories using a Markov Chain approach. In Markov Chain, the maneuver
of motorcycle will described by state transition. The state transition model is depend
on probability function which will use for determine what action will be executed next.
The maneuver of motorcycle using Markov Chain model was validated by comparing
the analytical result with the naturalistic data, with similarity is calculated using MSE.
In order to know how good our proposed method can describe the maneuver of mo-
torcycle, we try to compare the MSE of the trajectory based on Markov Chain model
with those using polynomial approach. The MSE results showed the performance of
Markov Chain Model give the smallest MSE which 0.7666 about 0.24 better than 4th
order polynomial.
Copyright c 201x Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Rina Mardiati
Department of Electrical Engineering, UIN Sunan Gunung Djati Bandung
Jl. A.H. Nasution No. 105 Bandung 40614, Indonesia
r mardiati@uinsgd.ac.id
1. INTRODUCTION
Today, Indonesian transportation problems are increasingly being encountered in our daily life. Sev-
eral economic and social motivations can be related to the need to minimize the time spent in motorcycle for
transportation and consequently their related pollution problems. An additional problem worth mentioning is
the need to reduce traffic accidents, a human and social cost that is related not only inadequate driving, but also
to the planning of the flow conditions [1]. Due this motivations, the literature on traffic phenomena is already
vast and characterized by contributions covering modeling aspects, statement of problems, qualitative analysis,
and particularly developed simulation generated by applications. Continuing this efforts, there are many litera-
ture of traffic flow theories and models have been developed, but researcher generally agree that modeling has
not yet reached a satisfying level. Study of traffic flow are become important since many reasons behind that,
such as: 1) it is necessary to develop traffic model which can describes the real phenomena, 2) traffic model
can support for developing intelligent transportation system (ITS) whose related with safety driving system, 3)
traffic model support for future issue about intelligent car [2]. So, there are many researchers who developed
intelligent transportation system in order to minimize the number of traffic accident [3] [4] [5].
Mixed traffic systems are dynamically complex since there are many parameters and variables that
influence the interactions between the different kinds of motorcycles. These interactions can be described
as the behavior occurring in traffic. Vehicle behavior is influenced by internal and external factors. Internal
Journal Homepage: http://iaescore.com/journals/index.php/IJECE
Institute of Advanced Engineering and Science
w w w . i a e s j o u r n a l . c o m
, DOI: 10.11591/ijece.v8i5.pp3149-3157
2. 3150 ISSN: 2088-8708
factors are the status of the motorcycle such as driver psychology, motorcycle position, steering angle, speed,
etc. Meanwhile, external factors are environmental conditions such as the position of other vehicles, road
borders, pedestrians, etc.
Modeling the behavior of the motorcycle is still being continuously developed, especially in devel-
oping countries which have the characteristics of mixed traffic. To get a better understanding of motorcycle
behavior, one can look at maneuvers performed by drivers. Maneuver here can also be called as a movement
performed by the motorcycle which is a part of motorcycle’s movement to change a lane and also to avoid
obstacles or slower vehicle in front of him.
Modeling the maneuver that can adequately simulate actual situations has many benefits, especially to
solve problems in the field of transportation. Modeling of maneuvers can also describe how a driver interacts
within a traffic system. In order to reach this goal, various methods have been developed to obtain a model
that can adequately simulate actual situations. Based on the literature, several methods have been proposed for
modeling vehicle movement, such as: Rule Based Model [6], Cellular Automata [7] [8] [9], and Social Force
Model [10] [11] [12]. Each method has its own deficiencies and advantages. Rule Based Model is quite good
at describing vehicle maneuvers in traffic but it only works well at low traffic density. Problems will occur
when Rule Based Model is implemented on high-density traffic systems, making the simulation behave in an
unrealistic manner. Celullar Automata (CA) describes vehicle maneuvers better than the rule-based system but
has the disadvantage that its position updating rules are deterministic. Lately, Social Force Model (SFM) has
been applied to describe vehicle maneuvers and it performed better than both Rule Based Model and Celullar
Automata. SFM can describe the movement of vehicles based on a vector-based approach. In SFM, which
includes a movement model and the decision-making process of the driver, vehicle behavior is described by
the sum of several vector forces (acceleration force, repulsive force and attractive force). Although SFM can
describe vehicle movement better than Rule Based or CA, this method does not input some parameters that
have a large effect on achieving a realistic model, such as driver psychology or a probabilistic model for driver
characteristics.
Markov Chain was broadly use for modeling traffic for different purposes, such as to reduce vehicle
emission [13], short-term traffic flow forecasting [14], modeling the multi-traffic signal-control synchronization
[15], traffic state prediction [16], travel time estimation [17], etc. However, no one has modeled the motorcycle
maneuver using the Markov Chain model. In this research, we tried to build a model of motorcycle movement
which only focused on maneuver action to avoid the obstacle along with the trajectories using a Markov Chain
approach. In Markov Chain, the maneuver of motorcycle will described by state transition. The state transition
model is depend on probability function which will use for determine what action will be executed next. The
maneuver of motorcycle using Markov Chain model was validated by comparing the analytical result with the
naturalistic data, with similarity is calculated using MSE. In order to know how good our proposed method can
describe the maneuver of motorcycle, we try to compare the MSE of the trajectory based on Markov Chain
model with those using polynomial approach that has been done in previous research [18].
This paper is organized as follows. In Section 2, modeling motorcycle maneuvers using a Markov
chain process is presented. The simulation and analysis of applying this model are discussed in Section 3.
Finally, in Section 4 this paper is concluded by stating that the Markov chain process can be implemented in
modeling motorcycle movement trajectories for certain maneuvers.
2. THE PROPOSED METHOD
This research tries to build a model of maneuver behavior along with the trajectories using a Markov
Chain approach. In a Markov Chain process, the driver will make decisions to determine what actions will be
carried out in a certain environment. Vehicle α will be in a certain position, moving at a certain speed and
steering angle at time t, denoted as motorcycle state α (internal information). Next, motorcycle α will receive
external information from its environment, such as the positions and velocities of vehicles around it, for further
processing to determine what action is to be taken by motorcycle α. There are several steps must be executed
to build a motorcycle maneuver model using Markov Chain: 1) Define set of states and actions, 2) Define the
transition probability function, and 3) State mapping function.
2.1. Set of States and Actions
A state is the condition or status of motorcycle agent, which is a function of position (x, y), speed (v)
and direction of steering maneuvers (θ). Meanwhile, action is described by a function of the maneuver m ∈
IJECE Vol. 8, No. 5, October 2018: 3149 – 3157
3. IJECE ISSN: 2088-8708 3151
{0,1,2} with 0, 1, and 2 corresponds to no maneuver, right maneuver, and left maneuver respectively. Similarly,
acceleration a ∈ {0,1,2} with 0, 1, and 2 corresponds to fixed speed, acceleration, and deceleration.
In the Markov Chain process, the action of the motorcycle is determined by the probability of a
transition states. There are ten states to describe the movement of motorcycle, along with nine actions. The set
of actions (Ai) and states (Si) that are used for the motorcycle maneuvers can be seen in Table 1.
Table 1. Set of States and Actions
States Definition Actions Definition
S0 Vehicle with speed 0 km/h A1 Increases speed with no maneuver
S1 Vehicle with speed 3 km/h A2 Increases speed with right maneuver
S2 Vehicle with speed 6 km/h A3 Increases speed with left maneuver
S3 Vehicle with speed 9 km/h A4 Decreases speed with no maneuver
S1L Vehicle at a speed of 3 km/h with left steering angle A5 Decreases speed with right maneuver
S2L Vehicle at a speed of 6 km/h with left steering angle A6 Decreases speed with left maneuver
S3L Vehicle at a speed of 9 km/h with left steering angle A7 Decreases speed with right maneuver
S1R Vehicle at a speed of 3 km/h with left steering angle A8 Fixed velocity with right maneuver
S2R Vehicle at a speed of 6 km/h with left steering angle A9 Fixed velocity with left maneuver
S3R Vehicle at a speed of 9 km/h with left steering angle
2.2. Transition Probabilities
A maneuver is the movement to change the direction of a vehicle to move from one lane to another.
Maneuvers in this study are influenced by several parameters, including the internal state of the vehicle as well
as the external conditions, as shown in Figure 1.
dαβ
vβ
dβ1
DBrDBl
vβ1
wβ
DOV
DOH
Vehicle β
Vehicle β1 Vehicle α
WR
Figure 1. Illustration of Maneuver’s Parameters
The parameter in Figure 1 are dαβ, vβ, wβ, dβ1
, dβ2
, . . . , dβn
, vβ1
, vβ2
, dαBr
, dαBl
, DOH, DOV , and
WR. Where dαβ is a distance between motorcycle α and vehicle β, vβ is speed of vehicle β, wβ is the width of
vehicle β; (dβ1
, dβ2
, . . . , dβn
), distance between motorcycle α and vehicles to the left and right, vβ1
is a speed
of vehicle to the left, vβ2 is speed of vehicle to the right, dαBr is the distance between vehicle α and the right
border, dαBl
, distance between vehicle α and the left border, DOH is a horizontal offset distance to objects that
are in front of the vehicle, DOV is the vertical offset distance to vehicles to the left or the right of the vehicle,
and WR is the width of road.
There are two steps performed to build the transition probability function. Firstly, to model the prob-
ability of maneuverability function of the rider. Secondly, to model the probability of maneuvering direction
(left or right) to be taken by the motorcycle.
2.2.1. Transition Probability of Vehicle Maneuvers
The biggest factor that influenced the maneuver is if there is an obstacle in front of the motorcycle. As
function to model the desire of maneuvering of the driver, negative exponential function can be used to obtain a
great value for small distances and a small value for large distances. In addition, a critical distance factor (Dc)
should be added, which represents the critical distance where the motorcycle must do maneuver. If a maneuver
Vehicle Movement Model Based on Markov Chain Process in Mixed Traffic (Rina Mardiati)
4. 3152 ISSN: 2088-8708
cannot be carried out for example because there are vehicles to the right and left, then the action is decelerate
the speed. The maneuver intention probability of motorcycle α stated as Pα can be expressed as follows.
Pα =
e−k1(dαβ −Dc)
, for dαβ > Dc
1, for dαβ ≤ Dc
(1)
Where dαβ is the distance between motorcycle α and the vehicle in front of it (vehicle β), Dc is represents the
critical distance where the motorcycle must do maneuver or decelerate the speed, k1 is a constant that shows
an increased slope rate of a negative exponential curve as a function of the distance between the two vehicles.
Physically, a small value of k1 indicates that the driver wants to maneuver despite the distance to the vehicle in
front still being quite large (alert driver), while a high value of k1 indicates that the driver wants to maneuver
when the distance to the vehicle in front is already very small (a driver who is reluctant to maneuver unless
pressed).
2.2.2. Probability Estimation of Maneuver Direction
When the decision to maneuver based on Pα exceeds a certain threshold value, the next step is mod-
eled the optimum maneuver direction. The possible directions for the maneuver are determined by the condition
of the road, the borders to the right and left, and other vehicles in the vicinity. In this subsection, we build ma-
neuver direction probability model for six scenarios that commonly occur in traffic, as shown in Figure 2. This
scenario is still possible to be developed further in a follow-up study, which will be tailored to observations in
the field and processing the data obtained. The derivation process of the probability model has been done in a
previous research [18].
Table 2. Maneuver Direction Probabilities
Scenario Probability of Maneuver Direction
There are no obstructions on the left nor right
PθL
= µ · e
k3·
(dαBl
−dCl
)
WR
−k2·γl
PθR
= µ · e
k3·
(dαBr
−dCr
)
WR
−k2·γr
There is an obstruction to the right of the motorcyle
PθL
= µ · e
k3·
(dαBl
−dCl
)
WR
−k2·γl
PθR
=
1 − e−k4(dβ1
−dβ1C
)
, for dβ1
> dβ1C
0 , for dβ1 ≤ dβ1C
There is an obstruction to the left of the motorcycle
PθL
=
1 − e−k5(dβ1
−dβ1C
)
, for dβ1
> dβ1C
0 , for dβ1
≤ dβ1C
PθR
= µ · e
k3·
(dαBr
−dCr
)
WR
−k2·γr
There are obstruction to the right and to the left of the motorcycle
PθL
=
1 − e−k5(dβ1
−dβ1C
)
, for dβ1
> dβ1C
0 , for dβ1
≤ dβ1C
PθR
=
1 − e−k4(dβ1
−dβ1C
)
, for dβ1 > dβ1C
0 , for dβ1 ≤ dβ1C
There is a border on the left or on the right
PθL
= 0
PθR
= 1
There are boarders and obstructions
PθL
= µ · e
k3·
(dαBl
−dCl
)
WR
−k2·γl
PθR
=
1 − e−k4(dβ1
−dβ1C
)
, for dβ1 > dβ1C
0 , for dβ1 ≤ dβ1C
Table 2 shows the maneuver direction probability function. PθL
denotes the probability of a left
direction maneuver and PθR
denotes the probability of a right direction maneuver, with k2, k3, k4 and k5
as constants. Parameter γ denotes as a function of horizontal offset distances to objects that are in front of
motorcycle α (DOHl
, DOHr
), where wβ = dOHl
+ dOHr
, γl =
DOHl
DOHl
+dOHr
and γr =
DOHr
DOHl
+DOHr
. dCr
and dCl
denotes critical distance with motorcycle on the left and right. The µ value can be set to the value that
describes the habits of maneuvering direction of Indonesian driver.
IJECE Vol. 8, No. 5, October 2018: 3149 – 3157
5. IJECE ISSN: 2088-8708 3153
2.3. State-Mapping Function
After the transition probability function were determined, then we need to build a mapping func-
tion which describes the state-action mapping of decision making behavior of driver. Mathematically, this is
expressed by
P(St+1|St, Sβ1
, Sβ, Sβ3
, · · · , m, a) = P(Si+1|St, m, a) (2)
with P(Si+1|Si, mi, ai) denotes probability function of maneuver and acceleration at time t.
(a) (b) (c)
(d) (e) (f)
Figure 2. Traffic Scenario
3. RESEARCH METHOD
The research method consists of three main steps: 1) Data preprocessing, 2) Simulation, and 3) Com-
paring the simulation results with actual data. Data preprocessing was begin with doing the naturalistic obser-
vation using video streaming which ensures that the normal behavior can be observed and the data collected
are not affected by the presence of researchers. Next, in order to obtained pixel coordinate which represents
motorcycle’s trajectory, coordinates transformation to convert the pixel coordinate to real-world coordinate as
we seen on Figure 3. The preprocessing of data in this research is similar to those in our previous research [18].
(a) (b) (c)
Figure 3. The flow of data preprocessing, (a) Targeted motorcycle; (b) Maneuvers trajectory; (c) Photo coordi-
nate in a pixel
4. SIMULATION RESULTS AND DISCUSSION
The simulation results show that motorcycle movement modeling based on a Markov Chain process
was successfully implemented. The Markov Chain model was evaluated by looking at a plotting diagram.
There are three diagrams in Figure 4 which describes that Markov Chain was successfully implemented to
modeled the manuever of motorcycle (a maneuver diagram, a state transition diagram, and an acceleration
diagram). In Figure 4 (a), the changes of each state and speed for every vehicle during the simulation period
can be seen clearly. The blue motorcycle change his state in order to get a savely driving. Besides, Figure 4
(c), we can see the behavior of the blue motorcycle making three times maneuver during simulation time, at the
5th
, the 19th
, and the 40th
time step of the duration. In that time, the blue motorcycle sees a vehicle in front of
Vehicle Movement Model Based on Markov Chain Process in Mixed Traffic (Rina Mardiati)
6. 3154 ISSN: 2088-8708
him and try to avoid the vehicle by making a maneuver, while considering the border beside him to calculate
the maneuver probability.
The performance of Markov Chain model is verified by comparing actual maneuver trajectory with
the trajectory from Markov Chain model. Figure 5 (a) shows the actual trajectory data of ten motorcycle’s
that has taken independently at different time but plotted in one figure. It is interesting to note that there
are different types of maneuver style in that trajectory, for example motorcycle 1 makes a complex maneuver
pattern as to avoid the obstacle. In the other hand, motorcycle 3 and motorcycle 6 take a simple maneuver with
considerable distance to complete this maneuver. Figure 5 (b) shows the track of Markov Chain model using
(a) (b) (c)
Figure 4. Markov Chain simulation, (a) State-transition diagram; (b) Acceleration diagram; (c) Maneuver
decision diagram
that only accommodate one maneuvering angle which is 45◦
. We observed in this figure that Markov Chain
model successfully follow the trend of actual maneuver but cannot produce a smooth pattern. To improve the
situation, in Figure 5 (c), we add additional states of maneuver steering angle which are 22.5◦
, 45◦
, 62.5◦
to
accommodate a smoother trajectory pattern which is very close to the actual one. As a comparison we plot the
curve fitting of the track using static polynomial fitting which are 2nd
order polynomial, 3rd
order polynomial,
and 4th
order polynomial as shown in Figure 5 (d) (e) (f). In those figures, we observed that polynomial can
fit the actual trajectory as far as the trajectory is short and simple curve such as the maneuver of motorcycle
2, 4, and 9. However, polynomial fitting has difficulty to track a complex maneuver such as the maneuver of
motorcycle 1. This polynomial fitting also cannot track the slight maneuver such as maneuver of motorcycle 7
and 10.
IJECE Vol. 8, No. 5, October 2018: 3149 – 3157
7. IJECE ISSN: 2088-8708 3155
(a) (b) (c)
(d) (e) (f)
Figure 5. Manually track of ten different motorcycle’s maneuver, (a) actual motorcycle’s maneuver track
(b) approximation of maneuver’s track using Markov Chain with θ = 45◦
(c) approximation of maneuver’s
track using Markov Chain with θ = 22.5◦
, 45◦
, 62.5◦
(d) approximation of maneuver’s track using 2nd
order
polynomial (e) approximation of maneuver’s track using 3rd
order polynomial (f) approximation of maneuver’s
track using 4th
order polynomial
Performance of each fitting method is shown in Table 3. In Table 3, we observed that Markov Chain
model give the smallest MSE which 0.7666 about 0.24 better than 4th
order polynomial. Even though in
most cases the Markov Chain model using 22.5, 45, 62.5 has better MSE but in particular case, for example
in motorcycle 6, the performance of this model is worse than polynomial fitting, since the maneuver is very
complex.
Table 3. Mean Square Error of Motorcycle Maneuver Trajectory Tracking
Vehicle 2nd
order 3rd
order 4th
order θ = 45◦
θ = 22.5◦
, 45◦
, 62.5◦
1 2.7076 2.6887 2.1865 1.8073 0.6907
2 0.0849 0.0640 0.0626 0.4998 0.1472
3 1.0267 0.8822 0.8655 1.6302 0.4086
4 0.2525 0.2521 0.2509 0.9108 0.4336
5 0.8472 0.8092 0.6743 1.1847 0.2783
6 1.7213 1.3810 1.2796 3.8066 2.3199
7 1.9405 1.9405 1.9344 2.0455 0.6516
8 1.4145 1.4056 1.3684 2.0102 0.5179
9 0.2622 0.2022 0.1966 2.0889 0.7340
10 2.1705 1.6028 1.2978 3.8687 1.4841
Average 1.2428 1.1228 1.0117 1.9853 0.7666
5. CONCLUSION
In this research, a simple model based on a Markov Chain process was implemented to describe
motorcycle maneuver using ten states and nine actions. Besides, the probability function of maneuver intention
Vehicle Movement Model Based on Markov Chain Process in Mixed Traffic (Rina Mardiati)
8. 3156 ISSN: 2088-8708
was introduced in six scenarios which integrated to the state-mapping function of Markov Chain Model. The
maneuver of motorcycle using Markov Chain model was verified by comparing the analytical result with the
naturalistic data which give small MSE. This methods also compare with static polynomial fitting to know how
good is Markov Chain can describe a motorcycle maneuver movement. As a result, we found that MSE of
Markov Chain model is smaller than static polynomial fitting approach.
ACKNOWLEDGMENT
The authors would like to thank the Indonesia Endowment Fund for Education (LPDP Indonesia) and
the Indonesian Ministry of Religious Affairs for their financial support of this study.
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BIOGRAPHY OF AUTHORS
Rina Mardiati received her Bachelor degree in Mathematics Education from Universitas Pen-
didikan Indonesia (UPI) in 2006 and Master degree in Electrical Engineering from Institut
Teknologi Bandung (ITB) in 2009. She is now a PhD student at the School of Electrical Engi-
neering and Informatics, ITB. Her research is in the fields of mathematical modeling, simulation,
traffic modeling and intelligent systems. She is affiliated with IEEE as a student member.
Bambang Riyanto Trilaksono received his Bachelor degree in Electrical Engineering from ITB,
and Master and Doctorate degrees from Waseda University, Japan. He is now a professor at the
School of Electrical Engineering and Informatics, ITB. His research interests include robust control,
intelligent control & intelligent systems, discrete event systems, control applications, telerobotics,
embedded control systems, and robotics.
Yudi Satria Gondokaryono Gondokaryono received his Bachelor degree in Electrical Engineering
from ITB, and Master and Doctorate degree from New Mexico State University. He is now an
Assistant Professor in School of Electrical Engineering and Informatics at School of Electrical
Engineering and Informatics, ITB. His research interests include human computer interaction, real-
time, and embedded systems.
Sony Sulaksono Wibowo received his Bachelor and Master degrees in Civil Engineering from
ITB, and Doctorate degree from Chualalangkorn University. He is now an assistant professor at the
Department of Civil Engineering, ITB. His research interests include travel behavior, public trans-
portation and transport planning, non-motorized transportation, transportation and the environment.
Vehicle Movement Model Based on Markov Chain Process in Mixed Traffic (Rina Mardiati)