- People would have more free time that could be spent working, relaxing, or socializing while in transit instead of focusing on driving.
- Public transportation usage may increase as self-driving cars could provide convenient door-to-door mobility.
- New types of businesses catering to passengers in self-driving vehicles may emerge, such as mobile offices or entertainment venues.
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.
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.
An autonomous car is an autonomous vehicle capable of fulfilling the human transportation capabilities of a traditional car. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input.
Under this topic i have described about the autonomous cars, on which worlds top automobile and tech giants are working like google, ford, BMW, audi etc.
Google Self Driving Cars
The Google Self-Driving Car is a project by Google that involves developing technology for autonomous cars. The software powering Google's cars is called Google Chauffeur. Lettering on the side of each car identifies it as a "self-driving car". The project is currently being led by Google engineer Sebastian Thrun, former director of the Stanford Artificial Intelligence Laboratory and co-inventor of Google Street View. Thrun's team at Stanford created the robotic vehicle Stanley which won the 2005 DARPA Grand Challenge and its US$2 million prize from the United States Department of Defense. The team developing the system consisted of 15 engineers working for Google, including Chris Urmson, Mike Montemerlo, and Anthony Levandowski who had worked on the DARPA Grand and Urban Challenges.
Legislation has been passed in four states and the District of Columbia allowing driverless cars. The U.S. state of Nevada passed a law on June 29, 2011, permitting the operation of autonomous cars in Nevada, after Google had been lobbying in that state for robotic car laws. The Nevada law went into effect on March 1, 2012, and the Nevada Department of Motor Vehicles issued the first license for an autonomous car in May 2012, to a Toyota Prius modified with Google's experimental driverless technology. In April 2012, Florida became the second state to allow the testing of autonomous cars on public roads, and California became the third when Governor Jerry Brown signed the bill into law at Google HQ in Mountain View. In July 2014, the city of Coeur d'Alene, Idaho adopted a robotics ordinance that includes provisions to allow for self-driving cars.
Videos
https://www.youtube.com/channel/UCCLyNDhxwpqNe3UeEmGHl8g
Research presentation on Autonomous Driving. Direction perception approach.
Research work by Princeton University group.
Note: Link given in the presentation
An autonomous car is a vehicle capable of sensing its environment and operating without human involvement. A human passenger is not required to take control of the vehicle at any time, nor is a human passenger required to be present in the vehicle at all. An autonomous car can go anywhere traditional cargoes and do everything that an experienced human driver does.
The Society of Automotive Engineers (SAE) currently defines 6 levels of driving automation ranging from Level 0 (fully manual) to Level 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation.
Autonomous vs. Automated vs. Self-Driving: What’s the difference?
The SAE uses the term automated instead of autonomous. One reason is that the word autonomy has implications beyond the electromechanical. A fully autonomous car would be self-aware and capable of making its own choices. For example, you say “drive me to work” but the car decides to take you to the beach instead. A fully automated car, however, would follow orders and then drive itself.
The term self-driving is often used interchangeably with autonomy. However, it’s a slightly different thing. A self-driving car can drive itself in some or even all situations, but a human passenger must always be present and ready to take control. Self-driving cars would fall under Level 3 (conditional driving automation) or Level 4 (high driving automation). They are subject to geofencing, unlike a fully autonomous Level 5 car that could go anywhere.
Tesla Autopilot is an advanced driver-assistance system feature offered by Tesla .That has lane centring, adaptive cruise control, self-parking, ability to automatically change lanes without requiring driver steering, and enables the car to be summoned to and from a garage or parking spot.
An autonomous car is an autonomous vehicle capable of fulfilling the human transportation capabilities of a traditional car. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input.
Under this topic i have described about the autonomous cars, on which worlds top automobile and tech giants are working like google, ford, BMW, audi etc.
Google Self Driving Cars
The Google Self-Driving Car is a project by Google that involves developing technology for autonomous cars. The software powering Google's cars is called Google Chauffeur. Lettering on the side of each car identifies it as a "self-driving car". The project is currently being led by Google engineer Sebastian Thrun, former director of the Stanford Artificial Intelligence Laboratory and co-inventor of Google Street View. Thrun's team at Stanford created the robotic vehicle Stanley which won the 2005 DARPA Grand Challenge and its US$2 million prize from the United States Department of Defense. The team developing the system consisted of 15 engineers working for Google, including Chris Urmson, Mike Montemerlo, and Anthony Levandowski who had worked on the DARPA Grand and Urban Challenges.
Legislation has been passed in four states and the District of Columbia allowing driverless cars. The U.S. state of Nevada passed a law on June 29, 2011, permitting the operation of autonomous cars in Nevada, after Google had been lobbying in that state for robotic car laws. The Nevada law went into effect on March 1, 2012, and the Nevada Department of Motor Vehicles issued the first license for an autonomous car in May 2012, to a Toyota Prius modified with Google's experimental driverless technology. In April 2012, Florida became the second state to allow the testing of autonomous cars on public roads, and California became the third when Governor Jerry Brown signed the bill into law at Google HQ in Mountain View. In July 2014, the city of Coeur d'Alene, Idaho adopted a robotics ordinance that includes provisions to allow for self-driving cars.
Videos
https://www.youtube.com/channel/UCCLyNDhxwpqNe3UeEmGHl8g
Research presentation on Autonomous Driving. Direction perception approach.
Research work by Princeton University group.
Note: Link given in the presentation
An autonomous car is a vehicle capable of sensing its environment and operating without human involvement. A human passenger is not required to take control of the vehicle at any time, nor is a human passenger required to be present in the vehicle at all. An autonomous car can go anywhere traditional cargoes and do everything that an experienced human driver does.
The Society of Automotive Engineers (SAE) currently defines 6 levels of driving automation ranging from Level 0 (fully manual) to Level 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation.
Autonomous vs. Automated vs. Self-Driving: What’s the difference?
The SAE uses the term automated instead of autonomous. One reason is that the word autonomy has implications beyond the electromechanical. A fully autonomous car would be self-aware and capable of making its own choices. For example, you say “drive me to work” but the car decides to take you to the beach instead. A fully automated car, however, would follow orders and then drive itself.
The term self-driving is often used interchangeably with autonomy. However, it’s a slightly different thing. A self-driving car can drive itself in some or even all situations, but a human passenger must always be present and ready to take control. Self-driving cars would fall under Level 3 (conditional driving automation) or Level 4 (high driving automation). They are subject to geofencing, unlike a fully autonomous Level 5 car that could go anywhere.
Tesla Autopilot is an advanced driver-assistance system feature offered by Tesla .That has lane centring, adaptive cruise control, self-parking, ability to automatically change lanes without requiring driver steering, and enables the car to be summoned to and from a garage or parking spot.
Autonomous car based on artificial intelligence which is used by google for replacing drivers in car. Which will leads to the driving into the next phase
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
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.
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.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
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.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
2. CONTENTS
• Introduction
• Definition
• History
• Technology Used
• Working
• Vehicular Communication
• Google Driverless Car
• Potential Advantages
• Potential Obstacles
• Conclusion
3. INTRODUCTION
• Autonomous car is an automated or autonomous vehicle capable
of fulfilling the main transportation capabilities of a traditional car
without human input.
• Suggested by Forbes magazine as one of the Five Most Disruptive
Innovation of 2015.
• Autonomous vehicles have enormous potential to allow for more
productive use of time spent in a vehicle and to reduce crashes,
costs of congestion, energy consumption, and pollution.
4. DEFINITION
• Autonomous means having the power for self-government.
• National Highway Traffic Safety Administration (NHTSA) has
created a five-level hierarchy to help clarify the concept of
autonomous vehicles.
5. HISTORY
• Experimentation started in 1920s;
• The first truly autonomous cars appeared in
the 1980s, with Carnegie Mellon University’s
Navlab and ALV projects in 1984.
• DARPA (Defense Advanced Research
Projects Agency) Grand Challenge 2005
fueled the development and research.
• Google has done notable work in this field
for past few years.
6. TECHNOLOGY USED
• Various technologies work in conjunction with each other to make
a car autonomous.
• LIDAR Sensors
• RADAR Detectors
• GPS
• INS
• Electromechanical Systems
• Software and Algorithm
7. LIDAR (LIGHT DETECTION AND RANGING)
• LIDAR is a remote-sensing technology that
measures distance by illuminating a target with a
laser and analyzing the reflected light.
• There are several major components to a Lidar
system:
1. Laser (600nm-1000nm)
2. Scanner and Optics
3. Photodetector and receiver electronics.
4. Position and Navigation System.
8. RADAR (RADIO DETECTION AND RANGING)
• Radar is the use of radio waves to detect and
monitor various objects.
• Automotive radar systems in the 77 GHz
domain are used in car .
• There are two primary methods :
1. The direct propagation method
2. The indirect propagation method or the
Frequency Modulated Continuous Wave
(FMCW) .
9. GPS (GLOBAL POSITIONING SYSTEM)
• Global Positioning System is a space-based satellite
navigation system that provides location and time
information anywhere on earth where there is an
unobstructed line of sight to four or more satellites.
• The current GPS consists of three major segments.
These are Space segment (SS), a control segment (CS),
and a User segment (US).
• All satellites broadcast at the same two frequencies,
1.57542 GHz and 1.2276 GHz.
10. INS (INERTIAL NAVIGATION SYSTEM)
• Inertial navigation system (INS) is a navigation aid that
uses a computer, motion sensors and rotation sensors to
continuously calculate the position, orientation, and
velocity of a moving object without the need for external
references.
• Includes computer, gyroscopes, and accelerometers
• Initially used in spacecraft, ships and airplanes.
11. ELECTROMECHANICAL SYSTEMS
• Electromechanical systems used to manipulate the
steering, throttle and breaking systems of the car by
receiving instruction from the computer.
• These system employs the use of solid state relay for
switching purposes,
• servo motors for gearing purpose,
• and pneumatic and hydraulic controls for breaking.
12. SOFTWARE AND ALGORITHMS
• Various software and algorithms are used in autonomous car One
such technique is SLAM which is abbreviation for Simultaneous
Localization and Map Building.
• Used for solving a problem as to if it is possible for an autonomous
vehicle to start in an unknown location in an unknown
environment and then to incrementally build a map of this
environment while simultaneously using this map to compute
absolute vehicle location.
13. WORKING
• Autonomous car use many technologies and different type of
sensors to sense the environment around it and make appropriate
decision.
• Many systems are already available that assist human driver like
ABS (Automatic Breaking System) , ACC (Automatic Cruise Control)
etc.
• Various technologies discussed above are used in conjunction to
control the car.
14. LIDAR SENSOR
• An array of laser beams is emitted by the system in all directions
and reflected scattered waves are sensed by on board sensor.
• This data is fed in to the computer which generates high precision
3D map of the surrounding environment.
• This accuracy of this map is in centimeters because the wavelength
of light used is very small and is able to reflect of all types of
surfaces and small objects.
• Mounted on the top of the car on a cylindrical enclosure which
rotates 360 degree .
15. RADAR DETECTORS
• There are usually RADAR detectors
provides various functions like Lane-
change assistance, blind spot
detection, side impact warning, cross-
traffic alert, and adaptive cruise
control.
• The radar detectors are usually
mounted on both ends of the car.
• 3 detectors in front of the car, 1
detector on rear end.
16. GPS
• It is used in determining the position of the car and creating route
to selected destination. It is the basis of all the maps that car uses
while on the road.
• GPS alone can’t be used to determine the location as it can be
wrong by several meters; the bad weather conditions such as rain
and fog also harm the precision.
• So along with GPS other systems are used to determine the
complete position.
17. INS
• Inertial navigation system in fitted in to the
car.
• Uses accelerometers and gyroscopes to
measure acceleration and angular
movement of car.
• Sometimes position estimator is also used
with these two sensor for more precision.
18. DIGITAL CAMERAS
• Cameras are used in the cars for motives other than finding the
right path for the car.
• The cameras help in identifying traffic signal, unexpected things
like animals or pedestrians. Cameras also help in recognizing
certain gestures which other sensors can’t comprehend like hand
waving, stop sign, and traffic cones.
• The camera is usually mounted on the rear view mirror.
19. ULTRASONIC SENSORS
• Ultrasonic sensors are mounted on
various sides of the car to detect
objects very near the car.
• These sensors provide parking
assistance, collision warning, lane
departure among other functions.
21. COMPUTER
• The data from all the above mentioned system is fed in to an on-board
Computer which process this data at high speed and with the help of highly
sophisticated software makes the required decision and sends the output to
electro-mechanical units like automatic steering, throttle and breaking
systems.
• This computer is also connected to the internet and GPS system to provide
real time monitoring and updates.
23. VEHICULAR COMMUNICATION
• Vehicular communication systems are a type of network in which
vehicles and roadside units are the communicating nodes,
providing each other with information
• Contain two types of nodes: vehicles and roadside stations. Both
are dedicated short-range communications (DSRC) devices works
in 5.9 GHz band with bandwidth of 75 MHz and approximate range
of 1000 m.
• The network support both private data and public communications
but higher priority is given to public communications.
• Wireless Access in Vehicular Environments (WAVE) 802.11p.
25. GOOGLE DRIVERLESS CAR
• Google Self-Driving Car is the real name of the project that
involves developing technology for autonomous cars, mainly
electric cars.
• The software powering Google’s cars is called Google Chauffeur.
Lettering on each car identifies it as a “self-driving car”.
• The project is led by Google Engineer Chris Urmson.
• Google cars have about $150,000 in equipment including a
$70,000 LIDAR system. The range finder is mounted on the top is a
Velodyne 64-beam laser.
26. VELODYNE 64-BEAM LASER
Sensor:
64 lasers/detectors
360 degree field of view
<2 cm distance accuracy
5-15 Hz field of view update
50 meter range for pavement
120 meter range for other objects
>1.3 M points per second
Laser: Class 1- eye safe
905 nm wavelength
~ 10 ns pulse width
Dynamic laser power selection for
larger dynamic range
Mechanical: 15V @ 4 amps
300 RPM-900 RPM spin rate
27.
28. RANGE OF SENSORS
The stereo cameras have an
overlapping region with a
horizontal field of view of
approximately 50 degrees, a vertical
field of view of approximately 10
degrees, and a maximum distance
of approximately 30 meters.
The localization camera has a
horizontal field of view of
approximately 75 degrees, a
vertical field of view of
approximately 90 degrees
and a maximum distance of
approximately 10 meters.
The laser has a horizontal field of
view of approximately 360
degrees, a vertical field of view
of approximately 30 degrees, and
a maximum distance of 100
meters.
The radar has a
horizontal field of view of
60 degrees and a
maximum distance of 200
meters.
29. POTENTIAL ADVANTAGES
• Fewer traffic collisions
• Roadway capacity will be increased
• Higher speed limit can be sets for autonomous cars
• Alleviation of parking scarcity
• Removal of constraints on the user of cars
• Vehicular Communication together with autonomous car
system will eliminate the need of traffic signal and other
traffic requirement.
• Smoother ride
• Increased human work efficiency
30. POTENTIAL OBSTACLES
• First problem is reluctance by individuals to relinquish control of their cars
• A car’s computer could potentially be compromised
• implementation of legal framework and establishment of government
regulations for self-driving cars.
• Self-driving cars could potentially be loaded with explosives.
• Susceptibility of car’s navigation system to different types of weather.
• Current road infrastructure may need changes for autonomous cars.
• diminish the use of public transport
• High Cost
31. CONCLUSION
• Future of transportation and mankind.
• Competition like DARPA and companies like Google,
Mercedes are fueling the development.
• The autonomous car have numerous advantages,
• Ever decreasing cost of technology, and involvement of big
automotive giants.
• 4 states in USA namely Nevada, Florida, California, and
Michigan, along with District of Columbia who have
successfully enacted laws addressing autonomous vehicles
.
32. REFERENCES
• http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/how-google-self-driving-car-works
• http://www.telegraph.co.uk/motoring/motoringvideo/11308777/How-do-driverless-cars-work.html
• http://www.extremetech.com/extreme/189486-how-googles-self-driving-cars-detect-and-avoid-obstacles
• http://www.forbes.com/sites/bigbangdisruption/2015/01/09/the-five-most-disruptive-innovations-at-ces-2015/
• http://www.techworld.com/news/personal-tech/volvo-reveals-how-its-driverless-cars-work-3599076/
• http://www.velodynelidar.com
• C. Stiller, U. Ozguner, and K. Redmill, “Systems for Safety and Autonomous Behaviors in cars: The DARPA challenge
experience”, February, 2007
• Anderson, James M., Nidhi Kalra, Karlyn D. Stanley, Paul Sorensen, Constantine Samaras and Oluwatobi A. Oluwatola.
Autonomous Vehicle Technology: A Guide for Policymakers. Santa Monica, CA: RAND Corporation, 2014.