accident control technique based on artificial intelligence system
#1

Abstract
It is observed that the most accidents occur due to the driverâ„¢s ignorance of traffic and safety rules for avoiding accidents we use various techniques in this paper the major technique which was used here is artificial intelligence system. In general, vehicle monitoring, tracking and such activities are done using separate systems and they require mechanical force as input. Speed is monitored using speedometer and for controlling speed mechanical force is required to decelerate it. Fuel level monitoring, proximity detection, battery monitoring, etc requires separate system.

This paper uses GPS (global positioning system), speedometer, gradient operators, image analyzers, traffic light detector, monitoring systems and so on. Gradient operators are used for edge detection. But the practical implementation of controlling road accidents is some what difficult when the system approaches a new source other than a driver. Thereby this paper gives a solution for road accidents with the practical possibilities.
By using some simple logics and by applying some efforts human lives can be saved and while comparing to the damaged vehicles in accidents the necessary equipments cost is lower. The uses of this paper are to save human lives and also to avoid damage to vehicles.

For more details just post here.
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#2
The main objective of the current research effort is to explore the applicability of using principles from the field of Intelligent Adaptive Control for the on-line management and control of transportation systems. The main objective of the current study is to explore the applicability of using principles from the field of Intelligent Adaptive Control for the on-line management and control of transportation systems.Intelligent adaptive control is a field that encompasses the computational procedures of Fuzzy Logic,Artificial Neural Networks, and Genetic Algorithms. The aim of intelligent control is to design robust and learning controllers operating in an uncertain environment with very limited mathematical knowledge of the controlled process principles, which makes it very much applicable to the control of transportation systems.

a neuro-fuzzy controller is developed for predictive feedback control.The controller is developed for a test network, and its effectiveness will be evaluated using simulation.The study is also expected to result in the development of a prototype neuro-fuzzy controller for the on-line management of transportation systems. focus will be on exploring the feasibility of implementing a neuro-fuzzy controller for predictive feedback control. In this approach, an ANN will be used to predict future travel time, and a fuzzy controller will then try to balance the predicted travel times (as obtained from the NN) on the alternate routes between a given O-D pair.

Select Test Network:
The main criteria will be would be the availability of a calibrated transportation model for the network, since this would ensure that Origin-Destination, along with basic geometric and traffic data, are available.

Develop CORSIM Model for the Test Network
a CORSIM model will be developed for the test network which will be used in the study to represent the real-world and also for evaluating the fuzzy controller.

Develop the Predictive NN Model
A NN model is developed for predicting network traffic conditions.use of a predictive NN model might be quite advantageous as the transport systems are quite complex. given the ability of NNs to approximate nonlinear functions

Develop the Fuzzy Logic Controller
There are three methods:
1)the controller is designed to emulate a human controller
2)based upon designing a heuristic fuzzy controller
3)the traffic network is modeled as a fuzzy system, and the controller is designed based upon the analysis of that system.

Evaluate the Effectiveness of the Developed Controller
effectiveness of the developed controller is evaluated by computing the time savings resulting from the use of the controller.
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#3
hello can u please me send report and ppt for this topic asap??? please sir...
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#4
The pdf in the above report has some details. You can use the information and the info from other sources for making the report
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#5
tell me abu accident identification with auto dialer
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#6
Please send me full paper
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#7
presented by:
S.V.V.LAKSHMI,B.SINDHU

[attachment=8814]
ACCIDENT CONTROLLER BASED ON ARTIFICIAL INTELLIGENCE SYSTEM
ABSTRACT:

It is observed that the most accidents occur due to the driver’s ignorance of traffic and safety rules,for avoiding accidents we use various techniques in this paper the major technique which was used here is artificial intelligence system. In general, vehicle monitoring, tracking and such activities are done using separate systems and they require mechanical force as input. Speed is monitored using speedometer and for controlling speed mechanical force is required to decelerate it. Fuel level monitoring, proximity detection, battery monitoring, etc requires separate system.
This paper uses GPS (global positioning system), speedometer, gradient operators, image analyzers, traffic light detector, monitoring systems and so on. Gradient operators are used for edge detection. But the practical implementation of controlling road accidents is some what difficult when the system approaches a new source other than a driver. Thereby this paper gives a solution for road accidents with the practical possibilities.
By using some simple logics and by applying some efforts human lives can be saved and while comparing to the damaged vehicles in accidents the necessary equipments cost is lower. The uses of this paper are to save human lives and also to avoid damage to vehicles.
AN OVERVIEW OF REGULATED VEHICLE
Our vehicle which can detect a position of its own and it detects the width of roads and other cars width by using a gradient operator. It will also detect the distance between other vehicle we have also constructed monitoring station with a special server within the distance of each 25km.Thereby every car’s computer gets connected with the sever using a wireless protocol CDMA (code division multiple access technique) technology.
Our server gets connected with the global positioning system which is popularly called as GPS. Our server holds a GPS receiver thereby all the cars which connected to the server can receive its position using GPS receiver.
Global Positioning System generally detects all the position but it couldn’t detect the cross roads and the distance between other cars. So that we get connected with the server were the entire car’s computer gets connected.
The process of server is to get the position of all the vehicles and it must calculate the distance between each vehicle. Distances between the neighboring vehicles are transmitted to each and every vehicle.
The function of computer is to perform deceleration when the distance of vehicle’s gets before the value of zero. When the distance is less than one artificial intelligent system performs deceleration. When the deceleration is performed coagulation of vehicle’s gets avoided.
Initially the vehicles propagate their position and then the server transmits their appropriate distance. Both the communication takes place using a wireless protocol named CDMA.
CAMERA
The camera is placed on the front & rear side of the vehicle. It shots the image and gives it to the analyzer. Both the front and rear images are analyzed separately. The function of the camera is only to shoot. If the required light intensity is lower it proposes it to the computer and computer increases the intensity of the light of the vehicle without notifying to the user’s knowledge.
FUNCTIONING OF THE SYSTEM
IMAGE ANALYSER

The image analyzer contains the bitmap image, which has to be processed to detect the presence of other vehicle, zebra crossing, traffic signals. Given an X-bit per pixel image, slicing the image at different planes (bit-planes) plays an important role in image processing.
EDGE DETECTION
One way to detect edges or variations within a region of an image is by using the gradient operator. There are several well-known gradient filters. In this experiment we use the canny edge detector, which are obtained by convolving the image with two kernels, one for each direction.
Edge is also detected to analyze the roads even the left corner ends, if ever the vehicle tends to cross the limit the function is given to the intelligent system. The intelligent system takes its own position and it holds the vehicle to run on its straight path without moving to the other path.
If ever any damage acquires in the road, intelligent system takes up the position and it moves the vehicle accordingly and also it would not make any harm to the other vehicles which are moving together.
This canny edge form is suitable for real time implementations in FPGA’s or DSP’s, or very fast embedded PCs. In this context, however, the regular recursive implementation of the canny operator gives a good approximation of rotational symmetry and it also gives a bias towards horizontal and vertical edges.
A field-programmable gate array (FPGA) is semi conductor device that can be configured by the customer or designer after manufacturing—hence the name "field-programmable". To program an FPGA you specify how you want the chip to work with a logic circuit diagram or a source code in a hardware description language (HDL). FPGA’s can be used to implement any logical function that an application-specific integrated circuit (ASIC) could perform, but the ability to update the functionality after shipping offers advantages for many applications.
FPGA is used only embedding our pc with the gradient operator and also according to the change in roadways HDL is also changed thereby the system identifies the edges clearly according to the corresponding variance in roads.
DECELERATION SYSTEM
The piston is embedded with the computer. When the edge is found to be closer the embedded piston is used by prompting suitable commands from the personal computer which is attached with the vehicle. A machine member driven by a hydraulic actuator may oscillate when the hydraulic actuator decelerates or stops. The degree of oscillation is a function of the machine member's ability to track a deceleration command, which ability varies with changes in the position of the machine member and the load force acting there on. To reduce the oscillation, a command that controls operation of the hydraulic actuator is filtered using a filter function that changes with the machine member's load. The load force exerted on the hydraulic actuator which in turn can be designated by fluid pressure that results from the hydraulic actuator. Preferably, the frequency of the filter function is varied inversely with the magnitude of the actuator load force. Thereby the vehicle gets decelerated to the required level and collision is avoided.i.e.no brakes are applied since it may disturb other vehicle which is following. ultimate aim of this deceleration system is to avoid collision without involving the function of brakes.
The deceleration system works under the priority. The vehicle which is moving with a high speed is decelerated or if vehicles have the same speed the random sequential order will be followed and order will be placed by the server from monitoring station. However the deceleration is performed on the vehicle when the edges are closer than the limit. unless the edges are closer the vehicle may move with the speed as the wish.
In this system the vehicle’s computer gets communicated among themselves without approaching the server. They communicate for knowing the speed of the other vehicle. Their mode of communication takes place through the satellite system GSM (Global System of Mobile communication) by knowing the speed of other vehicle it compares with its own speed if it is greater than other vehicle the computer decelerates its own vehicle.
ARTIFICIAL INTELLIGENCE
This paper has mounted a computer with artificial intelligent tools. When the driver fails to makes his duty properly. Artificial intelligence takes up the position. Here intelligence system is used in machine perception, voice speech system, analyzing the details given by the monitoring station, controlling deceleration process. Even a java Platform may employ for implementing the mentioned process
MACHINE PERCEPTION
` Machine perception is the ability to use input from sensors (such as cameras, microphones, sonar and others more exotic) to deduce aspects of the world. Computer visions the ability to analyze visual input. A few selected sub problems are speech recognition, and object recognition.
The objects are recognized and informed to the monitoring station. This recognisation part is successful in the image processing systems.
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