This document discusses using fuzzy logic for automated speed control in vehicles. Fuzzy logic is well-suited for control applications like traffic and temperature control. It can represent complex systems using fuzzy sets instead of binary logic. For vehicle speed control, fuzzy logic is used to sense obstacles using distance sensors and control the vehicle's speed based on the angle of the obstacle to prevent collisions. This system allows the vehicle to slow down or stop if obstacles subtend an angle greater than 60 degrees. Fuzzy logic control could help reduce accidents by taking over critical functions from human drivers.
This presentation includes what is fuzzy logic, characteristics, membership function with example, fuzzy set theory, De-Morgans Law, Fuzzy logic V/S probability, advantages and disadvantages and application areas of fuzzy logic. This is a presentation is useful for IT students.
Its ability to deal with vague systems and its use of linguistic variables. Leads to faster and simpler program development of system controllers. It can be a decision support system tool for managers.
This presentation includes what is fuzzy logic, characteristics, membership function with example, fuzzy set theory, De-Morgans Law, Fuzzy logic V/S probability, advantages and disadvantages and application areas of fuzzy logic. This is a presentation is useful for IT students.
Its ability to deal with vague systems and its use of linguistic variables. Leads to faster and simpler program development of system controllers. It can be a decision support system tool for managers.
How can you deal with Fuzzy Logic. Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in degree
between 0 and 1
An autonomous vehicle is a kind of vehicle which can drive itself to the destination without any human
conduction. This is also known as driverless vehicle, self-driving vehicle or robot vehicle. Autonomous
vehicles require the combination of various sensors to detect their surroundings and interpret the
information to identify the appropriate navigation path and the obstacles in the way.
Modern vehicles provide some autonomous features like speed controls, emergency braking or keeping
the vehicle into the lane. Here, differences remain between a fully autonomous vehicle on one hand
and driver assistance technologies on the other hand.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/nxp/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Tom Wilson, ADAS Product Line Manager at NXP Semiconductors, presents the "Sensing Technologies for the Autonomous Vehicle" tutorial at the May 2016 Embedded Vision Summit.
Autonomous vehicles will necessarily utilize a range of sensing technologies to see and react to their surroundings. We are witnessing dramatic advances not just for embedded vision, but also in complementary technologies like radar and LiDAR. Each of these sensing technologies provides unique capabilities for giving a vehicle a complete view of its surroundings. This presentation compares vision-based sensing with complementary sensing technologies, explores key trends in sensors for autonomous vehicles, and analyses challenges and opportunities in fusing the output of multiple sensor technologies to enable robust perception and mapping for autonomous vehicles.
The Fuzzy Logic is discussed with three simple example problems all solved in MATLAB
1. Restaurant Problem
2. Temperature Controller
3. Washing Machine Problem
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
How can you deal with Fuzzy Logic. Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in degree
between 0 and 1
An autonomous vehicle is a kind of vehicle which can drive itself to the destination without any human
conduction. This is also known as driverless vehicle, self-driving vehicle or robot vehicle. Autonomous
vehicles require the combination of various sensors to detect their surroundings and interpret the
information to identify the appropriate navigation path and the obstacles in the way.
Modern vehicles provide some autonomous features like speed controls, emergency braking or keeping
the vehicle into the lane. Here, differences remain between a fully autonomous vehicle on one hand
and driver assistance technologies on the other hand.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/nxp/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Tom Wilson, ADAS Product Line Manager at NXP Semiconductors, presents the "Sensing Technologies for the Autonomous Vehicle" tutorial at the May 2016 Embedded Vision Summit.
Autonomous vehicles will necessarily utilize a range of sensing technologies to see and react to their surroundings. We are witnessing dramatic advances not just for embedded vision, but also in complementary technologies like radar and LiDAR. Each of these sensing technologies provides unique capabilities for giving a vehicle a complete view of its surroundings. This presentation compares vision-based sensing with complementary sensing technologies, explores key trends in sensors for autonomous vehicles, and analyses challenges and opportunities in fusing the output of multiple sensor technologies to enable robust perception and mapping for autonomous vehicles.
The Fuzzy Logic is discussed with three simple example problems all solved in MATLAB
1. Restaurant Problem
2. Temperature Controller
3. Washing Machine Problem
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Fuzzy logic is often heralded as a technique for handling problems with large amounts of vagueness or uncertainty. Since its inception in 1965 it has grown from an obscure mathematical idea to a technique used in a wide variety of applications from cooking rice to controlling diesel engines on an ocean liner.
This talk will give a layman's introduction to the topic and explore some of the real world applications in control and human decision making. Examples might include household appliances, control of large industrial plant, and health monitoring systems for the elderly. We will look at where the field might be going over the next ten years, highlighting areas where DMU's specialist expertise drives the way.
Identification system of characters in vehicular platesIJRES Journal
In this paper, is proposed a system that identifies the location and dimensions of the characters
relative to the image of a vehicular plate, when the location of the plate has not been accurate. The system is
divided into 4 stages, each with a specific purpose. Which are: binarization by thresholding, morphological
filtering, identification of the largest area and segmentation similarity. The first stage is used to find at the extent
if possible, the region occupied by the plate relative to the rest of the image. Then, in the filtering step, it seeks
to eliminate as far as possible the noise that interferes with the identification of the characters. The third stage is
used to identify the region occupied by the plate. Finally, in the fourth and last stage the segmentation by
similarity is used to identify position and dimension of the characters in the image, in stage a Kohonen neural
network is used.
Pultrusion 101 - General capabilities of Creative Pultrusions, Inc., a leader in the fiber reinforced polymer composites industry. We are best in class and offer in-house design, manufacture of profiles, fabrication and cnc machining and in-house testing.
Series of powerpoint slides showing 6 different composite forming techniques: Hand lay-up, vacuum bagging, compression moulding, filament winding, pultrusion and resin transfer moulding. The slides are adapted from the University of Liverpool "Composite Materials" lectures [MATS311] by Prof. W. Cantwell.
AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM FOR INDIAN VEHICLE IDENTIFICATION ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license plate. The system is implemented on the entrance for security control of a highly restricted area like
military zones or area around top government offices e.g.Parliament, Supreme Court etc.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
Adaptive Cruise Control, Electronic Brake Force Distribution,Traction Control...Shubham Thakur
In this PPT All the modern controls are explained like
Adaptive Cruise Control, Electronic Brake Force Distribution,Traction Control System, Electronic Stability Control, Common Rail Direct Fuel Distribution, Turbocharged Direct Injection, Airbag
Embedded systems, especially in-vehicle embedded systems, are ubiquitously related to our everyday life. The development of embedded systems greatly facilitates the comfort of people’s life, changes our view of things, and has a significant impact on society
An Intelligent Approach To Braking System Using Artificial Neural NetworkRavina Dadhich
My presentation is all about increasing vehicle's class by adopting an intelligent approach to braking system using Artificial Neural Network.This approach will give high customer satisfaction and even reduces the chances of accidents. Ultimate driving experience can be felt out if your automobile is fitted with this braking technology.
This thesis describes an intelligent approach to control an Antilock Braking System (ABS) employing a fuzzy controller. Stopping a car in a hurry on a slippery road can be very challenging. Anti-lock braking systems (ABS) take a lot of the challenge out of this sometimes nerve-wracking event. In fact, on slippery surfaces, even professional drivers can't stop as quickly without ABS as an average driver can with ABS
An overview of embedded systems in automobilesLouise Antonio
This presentation on the applications of embedded systems in automobiles focusses on the two most prevalent and sought about technologies- ABS and ACC with collison avoidance, the biggest motivation being that these technologies save lives.This discusses the doppler shift in detail.
3. Abstract :
• Automobiles have become an integrated part
of our daily life.
• Due to the speed of automobiles now a days
highway accidents are happening frequently.
• The automated speed control system prevents
this accidents which is possible with FUZZY
LOGIC(artificial intelligence).
• This is based on obstacle sensor unit.
4. FUZZY LOGIC :-
• THIS LOGIC IS BEST SUITED FOR CONTROL
APPILICATIONS SUCH AS TRAFFIC, TEMPERATURE.
• FUZZY LOGIC SEEMS TO BE MOST SUCCESFULL IN
TWO CASES:-
1. Very complex models where understanding is
strictly limited, in fact, quite judgmental.
2. Processes where human reasoning, human
perception , or human decision making are inextricably
involved.
5. FUZZY LOGIC REPRESENTATION:-
Slowest(snail)
For every problem it
[ 0.0 – 0.25 ]
must represent in
terms of fuzzy sets.
Slow(tortoise)
[ 0.25 – 0.50 ]
For different speeds Fast(dog)
the logic differs from
[ 0.50 – 0.75 ]
each other.
Fastest(cheeta)
[ 0.75 – 1.00 ]
6. FUZZY LOGIC IN CONTROL
SYSTEMS:-
Fuzzy Logic provides a more efficient and resourceful
way to solve Control Systems.
Some Examples
Temperature Controller
Anti – Lock Break System ( ABS )
8. FUZZIFICATION AND DEFUZZIFICATION:-
• Fuzzification is the process of making a crisp
quantity fuzzy.
• Defuzzification is the conversion of a fuzzy
quantity to a precise quantity.
9. OBSTACLE SENSOR UNIT:-
• THIS SENSES THE DISTANCE OF OBSTACLE INFRONT
OF THE CAR.
• AS THE SPEED INCREASES THE SENSING DISTANCE
ALSO INCREASES.
• THE SPEED OF THE CAR IS TAKEN AS THE INPUT AND
THE DISTANCE SENSED BY THE SENSOR IS
CONTROLLED.
10. FROM THE GRAPH IT IS CLEAR THAT
THE SENSING DISTANCE ALMOST
VARIES LINEARLY WITH SPEED.
11. SPEED CONTROL:-
The speed of the car is
controlled according to the angle subtended by the
obstacle. The minimum angle it can overcome is 60 .
• SPEED BRAKER:-
• FLY OVER:-
12. OBSTACLES WHICH THE CAR CANNOT
OVERCOME:-
• At any instant, if the angle subtended by the obstacle is
greater than 60 , then the car comes to rest before
colliding with the obstacle.
13. The angle is taken as the i/p & the o/p speed is
controlled.
Input membership function:-
• From the graph it is clear that the speed
becomes zero when the angle of the obstacle
is greater than 60 .
14. • The rules are not only applicable to obstacles
but also small pit, subway etc,.
• Rear Sensing: This fuzzy control can be
extended to rear sensing by placing a sensor
at the back side of the car, and can be used to
control the motion of the car when the wheals
rotate in the opposite direction or when the
car is in rear gear.
15. APPLICATIONS:
• Auto car parking system
• Temperature Controller
• Anti – Lock Break System ( ABS )
17. CONCLUSION:-
• The fuzzy logic control system can relieve the
driver from tension and can prevent accidents.
• This fuzzy control unit when fitted in all the
cars can result in an accident free world.
18. FUTURE SCOPE
• Now it is using only in costly cars like
BENZ,BMW,AUDI etc..in future we can get it
for any cars.