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.
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
This is a presentation that focuses on autonomous vehicles technology. The presentation describes key sensor technologies integrated under the bonnet of a driverless car. After a brief introduction, the presentation dwells deeper into each sensor technology demonstrating examples of self driving cars such as Google's self driving car, DARPA URBAN challenge etc., along the way. It also introduces the concept of electronic control units which is responsible for collecting data from different sensors and respond to other units accordingly. The slides also build a platform for vehicle to vehicle communication technology, types and its application areas.
A self-driving car is a vehicle that is capable of sensing its environment and navigating without human input. Self-driving cars can detect surroundings, using a variety of techniques such as radar, GPS, and computer vision.
<<instagram>> https://www.instagram.com/mike_sarafoglou/
<<youtube>> https://www.youtube.com/channel/UCZQDCo6W-3wTkbrkHbgjs2w
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.
Research presentation on Autonomous Driving. Direction perception approach.
Research work by Princeton University group.
Note: Link given in the presentation
After decades of anticipation, practical self-driving cars are here. Drive.ai will deploy a self-driving car service for public use in Texas starting in July.
We can continue pushing self-driving forward by focusing on three key elements: industry-leading AI technology, local partnerships, and people-centric safety.
This Presentation describes about the concept of self driving car with uses of different technology. This presentation will be helpful for those who want to know about new technology and will also be helpful for those who want to give seminar in technical college.
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
This is a presentation that focuses on autonomous vehicles technology. The presentation describes key sensor technologies integrated under the bonnet of a driverless car. After a brief introduction, the presentation dwells deeper into each sensor technology demonstrating examples of self driving cars such as Google's self driving car, DARPA URBAN challenge etc., along the way. It also introduces the concept of electronic control units which is responsible for collecting data from different sensors and respond to other units accordingly. The slides also build a platform for vehicle to vehicle communication technology, types and its application areas.
A self-driving car is a vehicle that is capable of sensing its environment and navigating without human input. Self-driving cars can detect surroundings, using a variety of techniques such as radar, GPS, and computer vision.
<<instagram>> https://www.instagram.com/mike_sarafoglou/
<<youtube>> https://www.youtube.com/channel/UCZQDCo6W-3wTkbrkHbgjs2w
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.
Research presentation on Autonomous Driving. Direction perception approach.
Research work by Princeton University group.
Note: Link given in the presentation
After decades of anticipation, practical self-driving cars are here. Drive.ai will deploy a self-driving car service for public use in Texas starting in July.
We can continue pushing self-driving forward by focusing on three key elements: industry-leading AI technology, local partnerships, and people-centric safety.
This Presentation describes about the concept of self driving car with uses of different technology. This presentation will be helpful for those who want to know about new technology and will also be helpful for those who want to give seminar in technical college.
MEMS and Sensors in Automotive Applications on the Road to Autonomous Vehicle...Jari Honkanen
MicroVision's MEMS Laser Beam Scanning Technology applied to HUD and ADAS applications presentation by Jari Honkanen at the MEMS & Sensors Executive Congress 2016, Scottsdale, AZ, November 10-11, 2016
MEMS and Sensors in Automotive Applications on the Road to Autonomous Vehicle...MicroVision
MicroVision’s Director of Technical Marketing and Applications Development, Jari Honkanen was invited to speak at MSIG’s 12th annual MEMS & Sensors Executive Congress 2016 on MEMS and sensors as key enabling technologies in the automotive market. Honkanen also discussed the benefits of applying MicroVision’s MEMS scanned virtual image HUD and LIDAR sensor concept for ADAS applications.
autonomous car, self driving car, presentation on google driving car, sensor used in car , future car, four wheeler car , colloquium, mechanical engineering, engineering technology ,b.tech, automotive engineering, california based car, self control car
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.
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
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Essentials of Automations: Optimizing FME Workflows with Parameters
Autonomous Vehicles
1. AUTONOMOUS VEHICLES
PRESENTED BY:
YAMINI( 17001504026)
M.Tech. (M.E.)
AUTONOMOUS VEHICLES : A SEMINAR 1
A SEMINAR ON
DEENBANDHU CHHOTURAM UNIVERSITY OF SCIENCE
AND TECHNOLOGY, MURTHAL, SONIPAT (Hr.)
2. 1 INTRODUCTION AND HISTORY
2 TECHNOLOGY
3 DEVELOPMENT AND CURRENT SCENARIO
4 ADVANTAGES
5 DISADVANTAGES AND CHALLENGES
CONTENTS
AUTONOMOUS VEHICLES : A SEMINAR 2
3. INTRODUCTION
• Autonomous means self-governing
• An autonomous vehicle is one that can drive itself from a starting
point to a predetermined destination using various in-vehicle
technologies and sensors.
AUTONOMOUS VEHICLES : A SEMINAR 3
4. AUTONOMOUS VEHICLES : A SEMINAR
0
100000
200000
300000
400000
500000
600000
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Accidents in India
total raod accidents Total people killed
0
5
10
15
20
25
30
35
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Accident severity
4
• A 2015 National Highway Traffic Safety Administration report found that 94 percent of traffic accidents
happen because of human error.
• By taking humans out of the equation, self-driving vehicles are expected to make the roads much safer for
all.
INSPIRATION
SOURCE: Government Of India
Ministry Of Road Transport &
Highways Transport Research Wing
5. AUTONOMOUS VEHICLES : A SEMINAR
Two wheeler
34%
Auto rickshaws
6%
Cars,Jeeps,Taxis
24%
Buses
8%
Trucks,Tempos,Tractors
21%
Other motorised
vehicles
3%
Non Motorised vehicles
4%
SHARE OF ACCIDENTS BY TYPE OF VEHICLE IN PERCENTAGE
5
SOURCE: Government Of India
Ministry Of Road Transport &
Highways Transport Research Wing
6. AUTONOMOUS VEHICLES : A SEMINAR 6
HISTORY
1939 • General Motor’s exhibit
• Normal Bel Geddes created first self driving car which was an electric vehicle guided
by radio controlled electromagnetic fields generated with magnetized metal spikes
embedded in the roadway
By 1958 • GM made this concept a reality
• Car’s front end was embedded with sensors called pickup coils; they detect the
current flowing through a wire embedded in the road.
1977 • Japanese improved upon this idea using a camera system which processed image of
the road.
• Speed of this vehicle was below 20mph
Decade Later • Improvements from Germans in the form of VaMoRs, a vehicle outfitted with cameras
that could drive itself safely upto 56mph
As the technology improved, so did self- driving vehicle’s ability to detect and react to their environment.
7. The DARPA Grand Challenge
• The DARPA Grand Challenge is a prize competition for
American autonomous vehicles, funded by the Defense Advanced
Research Projects Agency, America.
• The initial DARPA Grand Challenge(2004) was created to spur the
development of technologies needed to create the first
fully autonomous ground vehicles capable of completing a substantial
off-road course within a limited time.
• The third event, the DARPA Urban Challenge(2007) extended the
initial Challenge to autonomous operation in a mock urban
environment.
• The most recent Challenge, the 2012 DARPA Robotic Challenge,
focused on autonomous emergency-maintenance robots.
AUTONOMOUS VEHICLES : A SEMINAR 7
8. 1
2 3
4 5
1950 - 2000
Safety/Convenience Features
2000 – 2010
Advanced Safety Features
2010 – 2016
Advanced Driver Assistance Features
2016 - 2025
Partially Automated Safety Features
2025+
Fully Automated Safety
Features
5 ERAS OF SAFETY
AUTONOMOUS VEHICLES : A SEMINAR 8NHTSA 2013
10. AUTONOMOUS VEHICLES : A SEMINAR 10
WHAT SHOULD AN AUTONOMOUS
VEHICLE DO?
1. Understand its immediate environment (PERCEPTION)
2. Find its way around obstacles and in traffic (MOTION PLANNING)
3. Know where it is and where it wants to go (NAVIGATION)
4. Take decisions based on current situation (BEHAVIOUR)
11. AUTONOMOUS VEHICLES : A SEMINAR 11
TECHNOLOGY
http://image-sensors-world.blogspot.com
12. RADAR
• RAdio Detection And Ranging
• RADAR can determine the velocity,
range and angle of objects.
• RADAR sensors can be classified per
their operating distance ranges:
Short Range Radar (SRR) 0.2 to 30m
range,
Medium Range Radar (MRR) in the
30-80m range and
Long Range Radar (LRR) 80m to more
than 200m range.
• Long Range Radar (LRR) is the sensor
used in Adaptive Cruise Control
(ACC)(system for road vehicles that
automatically adjusts the vehicle
speed to maintain a safe distance
from vehicles ahead.)
AUTONOMOUS VEHICLES : A SEMINAR 12
www.intellias.com
13. LIDAR
• Light Detection and Ranging
• LiDAR sensors measure the
distance to an object by
calculating the time taken by a
pulse of light to travel to an
object and back to the sensor.
• LiDAR can provide a 360° 3D view
of the obstacles that a vehicle
should avoid.
AUTONOMOUS VEHICLES : A SEMINAR 13
infograph.venngage.com
14. WHEEL SPEED SENSORS
• Active wheel-speed sensors are
an integral part of brake control
systems. They detect the
rotational wheel speed of
vehicles using a non-contacting
measurement principle.
• A wheel speed sensor or vehicle
speed sensor (VSS) is a type
of tachometer. It is a sender
device used for reading the speed
of a vehicle’s wheel rotation.
• The vehicle Speed sensor is also
used for the proper shifting up of
gears for the vehicle
maintenance.
AUTONOMOUS VEHICLES : A SEMINAR 14
www.hella.com
15. GPS
• Stands for "Global Positioning System."
GPS is a satellite navigation system
used to determine the ground position
of an object.
• The three main components are the
GPS satellites, the GPS receivers, and
the complex computer software
needed to decode the signals and
compute the geographical position of
the user.
• Up to 30 GPS satellites fly, mostly in
highly inclined (polar) orbits, at
altitudes around 20,000 km.
AUTONOMOUS VEHICLES : A SEMINAR 15
www.eso.org
16. ULTRASONIC SENSORS
• These are used for Blind Spot
detection as well as to detect nearby
objects or measure the position of
other vehicles during parking.
• These sensors are mounted on the
left rear wheel of a vehicle.
VIDEO CAMERAS
• Video cameras are installed at the
top of the front glass, near the rear
view mirror.
• These are used to detect the traffic
lights, traffic signs, pedestrians etc.
They also detect different road signs
like “ STOP” signs, zebra crossings,
sign Boards etc.
AUTONOMOUS VEHICLES : A SEMINAR 16
blog.nxp.com
17. HOW DO AN AUTONOMOUS VEHICLE WORK?
• Radar sensors dotted around the
car monitor the position of vehicles
nearby.
• Video cameras detect traffic lights,
read road signs and keep track of
other vehicles, while also looking
out for pedestrians and other
obstacles.
• Lidar sensors help to detect the
edges of roads and identify lane
markings by bouncing pulses of
light off the car’s surroundings.
• a central computer analyses all of
the data from the various sensors to
manipulate the steering,
acceleration and braking.
AUTONOMOUS VEHICLES : A SEMINAR 17
https://medium.com
18. VARIOUS AUTONOMOUS VEHICLES
AUTONOMOUS VEHICLES : A SEMINAR 18
AUTONOMOUS CAR
www.straitstimes.com
www.theverge.com
AUTONOMOUS MOTORCYCLE
RIDEABLE AUTONOMOUS DRONE
AUTONOMOUS BUS
AUTONOMOUS TRUCK
20. WHAT DO AUTHORS SAY?
• Johanna Zmud, Texas A&M University: Autonomous cars need to learn
how to drive just like people do: with real-world practice on public roads.
• Simone Pettigrew, Curtin University: A survey found very few are aware of
the social health benefits from the wide scale use of autonomous vehicles.
• Neil McBride, De Mantfort University: Far from setting us free,
autonomous vehicles are set to enable new forms of surveillance and
oppression.
• Giselle Rampersad, Flinders University: Do people really trust driverless
cars to carry them safely to their destinations? New research sows that we
are ready to use driverless cars in certain situations but not others,yet.
AUTONOMOUS VEHICLES : A SEMINAR 20
21. 16
5 2
4 3
REDUCED
ACCIDENTS
REDUCED TRAFFIC
CONGESTION
REDUCED TRAVEL
TIME
MORE EFFICIENT
PARKING
LOWER FUEL
CONSUMPTION
REDUCED CO2
EMISSIONS
ADVANTAGES
AUTONOMOUS VEHICLES : A SEMINAR 21
22. 16
5 2
4 3
Trusting a computer to
perform adequately
Autonomous vehicles
will be expensive
Potential to be
hacked
Learning new
technology
Increase in
unemployment rate
Sensors fail during
conditions out of the norm
DISADVANTAGES AND CHALLENGES
AUTONOMOUS VEHICLES : A SEMINAR 22
23. • Trepagnier et al., NAVIGATION AND CONTROL SYSTEM FOR AUTONOMOUS
VEHICLES, United States Patent, 2011
• I Barabás, A Todoruț, N Cordoș, A Molea, CURRENT CHALLENGES IN AUTONOMOUS
DRIVING , IOP Conf. Series: Materials Science and Engineering 252 (2017) 012096
• James M. Anderson, Nidhi Kalra, Karlyn D. Stanley, Paul Sorensen, Constantine
Samaras, Oluwatobi A. Oluwatola, AUTONOMOUS VEHICLE TECHNOLOGY- A GUIDE
FOR POLICYMAKERS
• Todd Litman ,Victoria Transport Policy Institute, AUTONOMOUS VEHICLE
IMPLEMENTATION PREDICTIONS IMPLICATIONS FOR TRANSPORT PLANNING ,2017
• ITS Digest, The World’s Forum For Intelligent Transportation System
• Autonomous Driving in Urban Environments: Boss and the Urban Challenge
AUTONOMOUS VEHICLES : A SEMINAR 23
REFERENCES
