This document discusses adaptive cruise control (ACC) systems which help drivers maintain a safe distance from vehicles ahead. [1] ACC uses sensors like radar or lidar to detect the speed and distance of nearby vehicles and controls braking/acceleration accordingly. [2] More advanced systems allow vehicles to communicate with each other via technologies like Bluetooth to coordinate speeds and braking, forming "platoons" of vehicles with minimized spacing between them for improved traffic flow. [3] While ACC helps relieve driver workload, challenges remain around high costs and ensuring drivers remain attentive with such assistive systems.
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.
2015 D-STOP Symposium session by Ram Mirwani of AWR/National Instruments.
Get symposium details: http://ctr.utexas.edu/research/d-stop/education/annual-symposium/
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.
2015 D-STOP Symposium session by Ram Mirwani of AWR/National Instruments.
Get symposium details: http://ctr.utexas.edu/research/d-stop/education/annual-symposium/
Describes basics of automotive radar, working principle and future development in automotive radar sector. Role of radar sensor in development of future ACC, ADAS system.
Among the recent advancements in car safety technologies, the adaptive cruise control feature is one of the most important and useful. It greatly minimizes the pressure of the driver as it helps to control the speed of the car and maintains a safe distance from other cars to avoid a crash. But still, this adaptive control should not be used in bad weather conditions and in tunnels as they might not work efficiently. So, if you want to know all about the adaptive cruise control system in your car, then give some time to watch the following slide show.
Describes basics of automotive radar, working principle and future development in automotive radar sector. Role of radar sensor in development of future ACC, ADAS system.
Among the recent advancements in car safety technologies, the adaptive cruise control feature is one of the most important and useful. It greatly minimizes the pressure of the driver as it helps to control the speed of the car and maintains a safe distance from other cars to avoid a crash. But still, this adaptive control should not be used in bad weather conditions and in tunnels as they might not work efficiently. So, if you want to know all about the adaptive cruise control system in your car, then give some time to watch the following slide show.
This presentation contains,
i. Basics of Control Systems,
ii. Wind Turbine Controls
iii. Basics about Wind Farm and Control
iv. Wind Turbine Gearbox
v. Wind Turbine Generator
vi. Grids
As Digital Still Cameras (DSC) become smaller, cheaper and higher in resolution, photographs are increasingly prone to blurring from shaky hands. Optical image stabilization (OIS) is an effective solution that addresses the quality of images, and is an idea that has been around for at least 30 years. It has only recently made its way into the low-cost consumer camera market, and will soon be migrating to the higher end camera phones. This paper provides an overview of common design practices and considerations for optical image stabilization and how silicon-based MEMS dual-axis gyroscopes with their size, cost and performance advantages are enabling this vital function for image capturing devices
Ijeee 20-23-target parameter estimation for pulsed doppler radar applicationsKumar Goud
Target Parameter Estimation for Pulsed Doppler Radar Applications
Pratibha Jha1 S.Swetha2 D.Kavitha3
M.Tech Scholar (ECE), Dept of ECE Senior Assistant Professor & Associate Professor, Dept of ECE
Aurora’s Scientific Technological &
Research Academy Aurora’s Scientific Technological &
Research Academy, JNTUH Aurora’s Scientific Technological &
Research Academy, JNTUH
Bandlaguda, Hyderabad, TS, India Bandlaguda, Hyderabad, TS, India Bandlaguda, Hyderabad, TS, India
pratibhajha1001@yahoo.co.in swetha.sirisin@gmail.com kavitadevireddy@gmail.com
Abstract- Conventional monostatic single-input single-output (SISO) radar transmits an electro-magnetic (EM) wave from the transmitter. The properties of this wave are altered while reflecting from the surfaces of the targets towards the receiver. The altered properties of the wave enable estimation of unknown target parameters like range, Doppler, and attenuation. However, such systems offer limited degrees of freedom. Multiple-input and multiple-output (MIMO) radar systems use arrays of transmitting and receiving antennas like phased array radars but while a phased array transmits highly correlated signals which form a beam, MIMO antennas transmit signals from a diverse set and independence between the signals is exploited
Keywords: radar, OTA, MIMO, FHSS, DSSS, MISO
In the modern age, High-resolution radar images can be achieved by employing SAR technique. It is well
known that SAR can provide several times better image resolution than conventional radars. The exploration for efficient
image denoising methods still remains a valid challenge for researchers. Despite the difficulty of the recently proposed
methods, mostly of the algorithms have not yet attained a pleasing level of applicability; each algorithm has its
assumptions, advantages, and limitations. This paper presents a review of synthetic aperture radar. Behind a brief
introduction in our work we are especially targeting the noise called backscattered noise in SAR terminology which
causes the appearance of speckle Potential future work in the area of air flight navigation, mapping Weather Monitoring
& during natural disaster like earth quake. The SAR having the capability, to make human visibility beyond optical
vision, is also discussed.
Automatic target detection and localization using ultra-wideband radarIJECEIAES
The pulse ultra-wide band (UWB) radar consists of switching of energy of very short duration in an ultra-broadband emission chain, and the UWB signal emitted is an ultrashort pulse, of the order of nanoseconds, without a carrier. These systems can indicate the presence and distances of a distant object, call a target, and determine its size, shape, speed, and trajectory. In this paper, we present a UWB radar system allowing the detection of the presence of a target and its localization in a road environment based on the principle of correlation of the reflected signal with the reference and the determination of its correlation peak.
Due to the increasing number of private cars in today's society, there are a lot of
safety problems in car reversing. This paper proposes a research program of ultrasonic
ranging car reversing radar system with higher accuracy and better warning effect. According
to the principle of ultrasonic ranging, the AT89C51 single-chip microcomputer is selected as
the core circuit, and the anti-interference error processing is adopted in the processing of the
single-chip microcomputer to solve the multiple measurement, the transmission time interval
and the dead zone measurement problem of the ultrasonic ranging. Car reversing radar
system based on ultrasonic ranging adopt transmitting and receiving circuit, will determine
the time difference in the single chip microcomputer. the results are sent to the digital display
circuit and voice broadcast circuit. Finally, it is verified by experiments that after ultrasonic
error measurement adopts error processing, under the complicated environmental conditions,
the accuracy of ranging is higher, the number of false alarms is reduced, and the device has
high reliability and practicability.
Implementation of Doppler Radar Based Vehicle Speed Detection Systemijtsrd
Nowadays, vehicular accidents have been increasing from day to day. Most of them are the cause of over speeding. This thesis describes the Arduino based vehicle speed detection system using Doppler radar. The primary goal of this system is to design of the vehicle speed detector using Doppler radar which is used to reduce the amount of accidents caused by over speeding. In this system, continuous wave CW Doppler radar which is a special case that only provides a velocity output is used as a sensor and the microcontroller is used to calculate the speed of the vehicle. Moreover, the amplifier is used to amplify the voltage level to drive the microcontroller as the sensor output is in micro volts. It is also included LCD display to indicate the speed level. A Doppler radar that can determine the frequency shift that occurs in electromagnetic waves due to the motion of scatters toward or away from the observer through measurement of the phase change that occurs in electromagnetic waves during a series of pulses. The Doppler frequency is negative for objects receding from the radar. The Doppler frequency is positive for objects approaching the radar. This system can be acceptable in real time applications because it is independent of temperature, humidity, noise airflow, dust, light, etc. The results of design are tested and follow through realization. Each of the implementation is evaluated and these evaluations lead to the conclusion that the design is able to achieve high accuracy of the speed. The major components of the design are Doppler radar HB100 , Arduino Uno, LCD display and LM324. C programming language is developed in this system. The results of this work can improve the performance of automobile safety system. May Zin Tun | Kay Thwe Zin "Implementation of Doppler Radar-Based Vehicle Speed Detection System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26653.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/26653/implementation-of-doppler-radar-based-vehicle-speed-detection-system/may-zin-tun
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
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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/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
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This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Cruise control devices
1. 101seminartopics.com
1. INTRODUCTION
Everyday the media brings us the horrible news on road accidents. Once a
report said that the damaged property and other costs may equal 3 % of the
world’s gross domestic product. The concept of assisting driver in longitudinal
vehicle control to avoid collisions has been a major focal point of research at
many automobile companies and research organizations. The idea of driver
assistance was started with the ‘cruise control devices’ first appeared in 1970’s
in USA. When switched on, this device takes up the task of the task of
accelerating or braking to maintain a constant speed. But it could not consider
the other vehicles on the road.
An ‘Adaptive Cruise Control’ (ACC) system developed as the next
generation assisted the driver to keep a safe distance from the vehicle in front.
This system is now available only in some luxury cars like Mercedes S-class,
Jaguar and Volvo trucks the U.S. Department of transportation and Japan’s
ACAHSR have started developing ‘Intelligent Vehicles’ that can communicate
with each other with the help of a system called ‘Co operative Adaptive Cruise
Control’ .this paper addresses the concept of Adaptive Cruise Control and its
improved versions.
2. 101seminartopics.com
2. ADAPTIVE CRUISE CONTROL (ACC)
2.1 PRINCIPLE OF ACC
ACC works by detecting the distance and speed of the vehicles ahead by
using either a Lidar system or a Radar system [1, 2].The time taken by the
transmission and reception is the key of the distance measurement while the
shift in frequency of the reflected beam by Doppler Effect is measured to know
the speed. According to this, the brake and throttle controls are done to keep the
vehicle the vehicle in a safe position with respect to the other. These systems are
characterized by a moderately low level of brake and throttle authority. These
are predominantly designed for highway applications with rather homogenous
traffic behavior. The second generation of ACC is the Stop and Go Cruise
Control (SACC) [2] whose objective is to offer the customer longitudinal
support on cruise control at lower speeds down to zero velocity [3]. The SACC
can help a driver in situations where all lanes are occupied by vehicles or where
it is not possible to set a constant speed or in a frequently stopped and congested
traffic [2]. There is a clear distinction between ACC and SACC with respect to
stationary targets. The ACC philosophy is that it will be operated in well
structured roads with an orderly traffic flow with speed of vehicles around
40km/hour [3]. While SACC system should be able to deal with stationary
targets because within its area of operation the system will encounter such
objects very frequently.
2.2 CONSTITUENTS OF AN ACC SYSTEM:
1. A sensor (LIDAR or RADAR) usually kept behind the grill of the vehicle to
obtain the information regarding the vehicle ahead. The relevant target data may
be velocity, distance, angular position and lateral acceleration.
3. 101seminartopics.com
2. Longitudinal controller which receives the sensor data and process it to
generate the commands to the actuators of brakes throttle or gear box using
Control Area Network (CAN) of the vehicle.
3. SENSOR OPTIONS:
Currently four means of object detection are technically feasible and
applicable in a vehicle environment [2]. They are
1. RADAR
2. LIDAR
3. VISION SENSORS
4. ULTRASONIC SENSOR
The first ACC system used LIDAR sensor.
3.1 LIDAR (Light Detection and Ranging)
The first acc system introduced by Toyota used this method. By measuring
the beat frequency difference between a Frequency Modulated Continuous light
Wave (FMCW) and its reflection [3].
Fig 1.Range estimation using FMCW-LIDAR
4. 101seminartopics.com
A company named Vorad Technologies has developed a system which
measured up to one hundred meters. A low powered, high frequency modulated
laser diode was used to generate the light signal.
Most of the current acc systems are based on 77GHz RADAR sensors.
The RADAR systems have the great advantage that the relative velocity can be
measured directly, and the performance is not affected by heavy rain and fog.
LIDAR system is of low cost and provides good angular resolution although
these weather conditions restrict its use within a 30 to 40 meters range.
3.2 RADAR (Radio Detection and Ranging):
RADAR is an electromagnetic system for the detection and location of
reflecting objects like air crafts, ships, space crafts or vehicles. It is operated by
radiating energy into space and detecting the echo signal reflected from an
object (target) the reflected energy is not only indicative of the presence but on
comparison with the transmitted signal, other information of the target can be
obtained. The currently used ‘Pulse Doppler RADAR’ uses the principle of
‘Doppler effect’ in determining the velocity of the target [5].
3.2.1 PULSE DOPPLER RADAR:
The block diagram of pulse Doppler radar is as shown in figure.2.
The continuous wave oscillator produces the signal to be transmitted and
it is pulse modulated and power amplified. The ‘duplexer’ is a switching device
which is fast-acting to switch the single antenna from transmitter to receiver and
back. The duplexer is a gas-discharge device called TR-switch. The high power
pulse from transmitter causes the device to breakdown and to protect the
5. 101seminartopics.com
receiver. On reception, duplexer directs the echo signal to the receiver. The
detector demodulates the received signal and the Doppler filter removes the
noise and outputs the frequency shift ‘fd’.
Fig2. Block diagram of pulse Doppler radar
3.2.2 EFFECT OF DOPPLER SHIFT:
The transmitter generates a continuous sinusoidal oscillation at
frequency ‘ft’which is then radiated by the antenna. On reflection by a moving
object, the transmitted signal is shifted by the Doppler Effect by ‘fd’.
If the range to the target is ‘R’, total number of wavelength is ‘λ’ in the two
way- path is given by,
n = 2R/ λ
The phase change corresponding to each λ =2π
So total phase change, p=2n П
=2(2R/ λ) π
So, if target moves, ‘R’ changes and hence ‘φ’ also changes.
6. 101seminartopics.com
Now, the rate of change of phase, or the ‘angular frequency’ is
W=dφ/dt =4 π (df/dt)/ λ
Let Vr be the linear velocity, called as ‘radial velocity’
Wd = 4 πVr/ λ =2πfd.
Fd=2Vr / λ
But λ = ft, the transmitted velocity.
Fd= (2c Vr)/ ft
So by measuring the shift, Vr is found. The ‘plus’ sign indicates that the
target and the transmitter are closing in. i.e. if the target is near, the echoed
signal will have larger frequency.
3.2.3 RADAR ANTENNA SCHEMES:
Radar systems employ a variety of sensing and processing methods to
determine the position and speed of vehicles ahead. Two such important
schemes are:
1. mechanically steered antenna
2. electronically steered antenna
1. Mechanically steered antenna:
A parabolic reflector is used as mechanically steered antenna. The
parabolic surface is illuminated by the source of energy placed at the focus of
the parabola. Rotating about its axis, a circular parabola is formed. A
symmetrical beam can be thus obtained. The rays originating from focus are
reflected parallel to the axis of parabola. [fig (3).]
7. 101seminartopics.com
Fig 3.Parabolic reflector antenna
2. Electronically steered phased array radar antenna
A phased array is a directive antenna made up of a number of individual
antennas, or radiating elements. The radiation pattern is determined by the
amplitude and phase of current at each of its elements. It has the advantage of
being able to have its beam electronically steered in angles by changing phase
of current at each element. The beam of a large fixed phased array antenna is
therefore can be rapidly steered from one direction to another without
mechanical positioning [1, 5].
Consider the following figure with ‘N elements placed (equally
separated) with a distance‘d’ apart. Suppose they have uniform response to
signals from all directions. Element ‘1’ is taken as reference with zero phase.
8. 101seminartopics.com
Fig 4. Phased array elements (example: reception of the beams)
From simple geometry, we can get difference between path lengths of
beam1 and that of beam2 is x = d sinθ, where ‘θ’ is the angle of incidence of
the beams. This gives phase difference between adjacent elements as Φ= 2π (d
sinθ)/ λ, where ‘λ’ is the wave length of the signal. But if the current through a
ferro electric element is changed, the dielectric constant ‘ε’ is changed since
electron density is changed, and for an electromagnetic radiation,
Φ = 2πx / λ
=2πxf/v,
here the velocity v = f λ
= 1/ (√μ ε)
Hence Φ=2πxf (√μ ε).
So if ‘ε’ is changed ‘Φ’ also changes and inserting ‘N’ phase shifting
elements to steer the beam, we can obtain an electronically steered beam.
Regardless of the scanning mechanism the radars typically operate in the
millimeter wave region at 76-77 GHz.
9. 101seminartopics.com
The system should be mounted inside the front grille of the car as shown
in figure (5). So its size is to be small. A typical radar produced by Delphi-
Delco Electronic systems is having the size of two stacked paper back
books(14x7x10 cm)[1].
3.3 FUSION SENSOR
The new sensor system introduced by Fujitsu Ten Ltd. and Honda
through their PATH program includes millimeter wave radar linked to a
640x480 pixel stereo camera with a 40 degree viewing angle. These two parts
work together to track the car from the non-moving objects. While RADAR
target is the car’s rear bumper, the stereo camera is constantly captures all
objects in its field of view.
Fig5. A prototype of a car with fusion sensor arrangement
10. 101seminartopics.com
Fig 6.Block diagram of sensing and controlling process
The image processor measures the distances to the objects through
triangulation method. This method includes an algorithm based on the detection
of the vertical edges and distance. Incorporating both the 16-degree field of
view of radar and 40-degree field of view of camera enhances the performance
in tight curves [4].
4. SPACE OF MANEUVERABILITY AND STOPPING
DISTANCE
The space of maneuverability is the space required by the driver to
maneuver a vehicle. An average driver uses larger sideways acceleration while
vehicle speed is low. If the curve radius of a possible trajectory is ‘r’ for a given
velocity ‘v’ and sideways acceleration ‘ay’ ,then r= / ay [2].so to get the
required ‘r’ ,when ‘v’ is low, ‘ay’ is also to be low correspondingly. The
11. 101seminartopics.com
stopping distance is given by, Ds = .5 u /ax + td u, where ‘u’ is the initial speed
‘td’ is the time taken by the system to receive and process the sensor data and
‘ax’ is the acceleration of the vehicle .the figure shows the detection of edges of
the preceding vehicles.
Fig 7.Detection of vehicle edges by the fusion sensor
5. CONTROLLER
The controller translates the situation into appropriate actions through
brake and pedal and throttle control actions.
Depending on the present traffic situation, two types of controls are possible.
1. Speed control
2. Headway control
If there is no vehicle presently in front, then the speed is controlled
about a set point just as in conventional cruise control. But in order to keep a
safe distance between the vehicle s, the headway control is required.
5.1ARTIFICIAL COGNITION
The conversion of raw information from sensors to control actions by the
two steps:-
12. 101seminartopics.com
1. Analyzing the traffic conditions
2. Deciding on a particular situation
The controller translates the desired situation into appropriate control
action through brake and throttle actuation.[2]. The controller concept is
simplified in the flow-diagram:
Fig 8.Flow diagram of controlling process
5.2. EXAMPLE OF ADAPTIVE CRUISE CONTROLLER
(MOTOROLA ACC)
The Motorola ACC constitutes a DSP module having MGT5200 which
provides a multiply-accumulator. The sensor data such as Radar information,
that from camera and an IR sensor are processed in it, to generate the input data
for the controller modules like HC12 and MPC565.[6].
13. 101seminartopics.com
Fig9. Motorola ACC
5.2.1 MPC565
It is a throttle controller or an engine speed controller. It consists of
the following features
1. SRAM (1MB to10 MB)
2. FLASH 1MB
3. EEPROM (4KB to 32 KB)
4. Real time clock
5. 4 x UART interfaces
6. 3 X CAN interfaces
7. 64-bit floating point unit.
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The MPC 565 can be programmed to generate the control signals
according to the sensor data. ‘The Phycore-MPC 565 developers’ are available
to program and develop the desired controller.
The throttle valve is actuated and the air intake is controlled so the
requirement of fuel for the right proportion with the air also increases. So more
fuel is injected and engine speed is changed.
5.2.2 HC12
The HC12 is a breaking controller which receives data from the wheel
speed sensors and from the DSP module. It generates the braking control signal.
5.2.3 CAN (Control Area Network) BUS
CAN BUS is the network established between microcontrollers. It is a2-
wire, half-duplex, high speed network for high speed high speed applications
with short messages. It can theoretically link up to 2032 devices on a network.
But today the practical limit is 110 devices. It offers high speed communication
rate up to 1Mbits per second and allows real time control. [7].
Each module in the ACC connected to the CAN is called ‘a node’. All are
acting as transceivers. The CAN bus carries data to and from all nodes and
provides quicker control transfer to each module.
The actuator used for throttle control is a solenoid actuator. The signal
through the coil can push or pull the plunger.
6. CO OPERATIVE ADAPTIVE CRUISE CONTROL
[CACC]
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Though conventional ACC and SACC are still expensive novelties, the
next generation called Cooperative ACC is already being tested. While ACC
can respond to the difference between its own behavior and that of the
preceding vehicle, the CACC system allows the vehicles to communicate and to
work together to avoid collision.[2,4].
Partners of Advanced Transit Highways (PATH) –a program of
California Department of Transportation and University of California with
companies like Honda conducted an experiment in which three test vehicles
used a communication protocol in which the lead car can broadcast information
about its speed, acceleration ,breaking capacity to the rest of the groups in every
20ms.
PATH is dedicated to develop systems that allow cars to set up platoons
of vehicles in which the cars communicate with each other by exchanging
signals using protocols like Bluetooth.
6.1. MAIN POSTULATIONS ABOUT CACC:
1. In CACC mode, the preceding vehicles can communicate actively with the
following vehicles so that their speed can be coordinated with each other.
2. Because communication is quicker, more reliable and responsive compared
to autonomous sensing as in ACC.
3. Because braking rates, breaking capacity and other important information
about the vehicles can be exchanged, safer and closer vehicle traffic is
possible.
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Fig 10.Under CACC, both the leading and following vehicles are
electronically “tied” to a virtual reference vehicle, as well as to each other.
7. ADVANTAGES
1. The driver is relieved from the task of careful acceleration, deceleration and
braking in congested traffics.
2. A highly responsive traffic system that adjusts itself to avoid accidents can
be developed.
3. Since the breaking and acceleration are done in a systematic way, the fuel
efficiency of the vehicle is increased.
DISADVANTAGES
1. A cheap version is not yet realized.
2. A high market penetration is required if a society of intelligent vehicles is to
be formed.
3. Encourages the driver to become careless. It can lead to severe accidents if
the system is malfunctioning.
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4. The ACC systems yet evolved enable vehicles to cooperate with the other
vehicles and hence do not respond directly to the traffic signals.
8. CONCLUSION
The accidents caused by automobiles are injuring lakhs of people every
year. The safety measures starting from air bags and seat belts have now
reached to ACC, SACC and CACC systems. The researchers of Intelligent
Vehicles Initiative in USA and the Ertico program of Europe are working on
technologies that may ultimately lead to vehicles that are wrapped in a cocoon
of sensors with a 360 –degree view of their surroundings. It will probably take
decades, but car accidents may eventually become as rare as plane accidents are
now, even though the road laws will have to be changed, upto an extent since
the non-human part of the vehicle controlling will become predominant.
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9. REFERENCES
1. Willie D. Jones, “Keeping cars from crashing.” , IEEE Spectrum September
2001.
2. P.Venhovens, K. Naab and B. Adiprasto, “Stop And Go Cruise Control”,
International Journal of Automotive Technology, Vol.1, No.2, 2000.
3. Martin D. Adams, “Co axial range Measurement-Current trends for Mobile
robotic Applications”, IEEE Sensors journal, Vol.2, no.1 Feb.2002.
4. http:// path.Berkeley.edu
5. Merril I.Skolnik, “Introduction To RADAR Systems.”Tata Mc Grawhill
edition 2001.
6. http://motorola /semiconductor.com
7. http://www.computer-solutions.co.uk
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ABSTRACT
The concept of assisting driver in the task of longitudinal vehicle control
is known as cruise control. Starting from the cruise control devices of the
seventies and eighties, now the technology has reached cooperative adaptive
cruise control. This paper will address the basic concept of adaptive cruise
control and the requirement to realize its improved versions including stop and
go adaptive cruise control and cooperative adaptive cruise control. The
conventional cruise control was capable only to maintain a set speed by
accelerating or decelerating the vehicle. Adaptive cruise control devices are
capable of assisting the driver to keep a safe distance from the preceding vehicle
by controlling the engine throttle and brake according to the sensor data about
the vehicle. Most of the systems use RADAR as the sensor .a few use LIDAR
also. Controller includes the digital signal processing modules and
microcontroller chips specially designed for actuating throttle and brake. The
stop and go cruise control is for the slow and congested traffic of the cities
where the traffic may be frequently stopped. Cooperative controllers are not yet
released but postulations are already there. This paper includes a brief theory of
pulse Doppler radar and FM-CW LIDAR used as sensors and the basic concept
of the controller.
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CONTENTS
1. INTRODUCTION
2. PRINCIPLE OF ACC
2.1 PRINCIPLE OF ACC
2.2 CONSTITUENTS OF AN ACC SYSTEM
3. SENSOR OPTIONS
3.1 LIDAR
3.2 RADAR
3.2.1 PULSE DOPPLER RADAR
3.2.2 EFFECT OF DOPPLER SHIFT
3.2.3 RADAR ANTENNA SCHEMES
3.3 FUSION SENSOR
4. SPACE OF MANEUVERABILITY AND STOPPING DISTANCE:
5. CONTROLLER
5.1ARTIFICIAL COGNITION
5.2. EXAMPLE OF ADAPTIVE CRUISE CONTROLLER
6. CO OPERATIVE ADAPTIVE CRUISE CONTROL [CACC]
6.1. MAIN POSTULATIONS ABOUT CACC
7. ADVANTAGES AND DISADVANTAGES
8. CONCLUSION
9. REFERENCES
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ACKNOWLEDGEMENT
I extend my sincere gratitude towards Prof. P.Sukumaran Head of
Department for giving us his invaluable knowledge and wonderful technical
guidance
I express my thanks to Mr. Muhammed Kutty our group tutor and also
to our staff advisor Ms. Biji Paul and Mr. Noushad V.M for their kind
co-operation and guidance for preparing and presenting this seminar.
I also thank all the other faculty members of AEI department and my
friends for their help and support.