TALLINNA TEHNIKAÜLIKOOL
Infotehnoloogia teaduskond
Informaatikainstituut
“Smart” cars
IDU0310
Internet of Things Solutions: Smart Devices,
Processes and Services
Student:
Ilja Rozanov
Student code:
103748
E-mail:
[email protected]
Tallinn
2014
Contents
Introduction .................................................................................................................................................... 3
Definition ......................................................................................................................................................... 4
Potential advantages and disadvantages ........................................................................................................ 5
Positive sides (+) ................................................................................................................................................. 5
Negative sides (-) ................................................................................................................................................ 6
Estimated Costs ................................................................................................................................................... 6
First driverless car ........................................................................................................................................... 7
The next generation vehicles .......................................................................................................................... 8
Google driverless car ..................................................................................................................................... 10
Today automotive systems ........................................................................................................................... 12
Advanced front-lighting system (AFS) ............................................................................................................. 12
Blind spot monitor............................................................................................................................................. 13
Lane departure warning system......................................................................................................................... 13
Collision avoidance system ............................................................................................................................... 14
Advanced Automatic Collision Notification ..................................................................................................... 14
Automotive night vision .................................................................................................................................... 15
Automatic parking ............................................................................................................................................. 16
Traffic Sign Recognition ................................................................................................................................... 16
Driver Monitoring System ................................................................................................................................ 16
Autonomous cruise control system ................................................................................................................... 17
GPS-aided autonomous cruise control system design scheme .......................................................................... 18
Autonomous car working scheme................................................................................................................. 19
Comparison of efficiency............................................................................................................................... 20
SWOT analysis of autonomous car................................................................................................................ 21
Future perspective and capabilities of autonomous car............................................................................... 22
Conclusion ..................................................................................................................................................... 22
Introduction
We live in an age of SMART devices. Most people have at their disposal or are familiar with smart devices,
such as - computers , smartphones, tablets , smart watches, smart homes , smart cars . From all this, the most
difficult technically and least common is smart cars. Smart devices are devices that use the latest
technological solutions (wi-fi, bluetooth , usb , different sensors) . In my project I examined closer SMART
cars their positive and negative sides, their technical condition, their capabilities now and in the future and
prospects of these cars in the future.
Smart-cars are mostly knows as autonomous car also known as a driverless car, driver-free car, selfdriving car or robot car. 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. Robotic cars exist mainly as
prototypes and demonstration systems. Autonomous vehicles sense their surroundings with such
techniques as radar, lidar, GPS, and computer vision. Advanced control systems interpret sensory
information to identify appropriate navigation paths, as well as obstacles and relevant signage. Some
autonomous vehicles update their maps based on sensory input, allowing the vehicles to keep track
of their position even when conditions change or when they enter uncharted environments.
Some quasi-autonomous demonstration systems date back to the 1920s and the 1930s. Since the
1980s, when Mercedes-Benz and Bundeswehr University Munich built a driverless car through the
EUREKA Prometheus Project, significant advances have been made in both technology and
legislation relevant to autonomous cars. Numerous major companies and research organizations
have developed working prototype autonomous vehicles, including Mercedes-Benz, General
Motors, Continental Automotive Systems, Autoliv Inc., Bosch, Nissan, Toyota, Audi, Volvo, Vislab
from University of Parma, Oxford University and Google. In 2010, four electric autonomous vans
successfully drove 8000 miles from Italy to China. The vehicles were developed in a research
project backed by European Union funding, by Vislab of the University of Parma, Italy. In July
2013 Vislab world premiered BRAiVE, a vehicle that moved autonomously on a mixed traffic route
open to public traffic. As of 2013, four U.S. states have passed laws permitting autonomous cars:
Nevada, Florida, California, and Michigan. In Europe, cities in Belgium, France and Italy are
planning to operate transport systems for driverless cars.
Definition
The term "autonomous" is not a generally accepted term in science when used to describe technical
artifacts. For example Wood et al. (2012), see reference below, writes: "This Article generally uses
the term “autonomous,” instead of the term “automated.” We have chosen to use the term
“autonomous” because it is the term that is currently in more widespread use (and thus is more
familiar to the general public). However, the latter term is arguably more accurate. “Automated”
connotes control or operation by a machine, while “autonomous” connotes acting alone or
independently. Most of the vehicle concepts (that we are currently aware of) have a person in the
driver’s seat, utilize a communication connection to the Cloud or other vehicles, and do not
independently select either destinations or routes for reaching them. Thus, the term “automated”
would more accurately describe these vehicle concepts". Wood, S.P., Chang, J., Healy, T. & Wood,
J. (2012).
In the United States, the National Highway Traffic Safety Administration (NHTSA) has established an
official classification system:
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Level 0: The driver completely controls the vehicle at all times.
Level 1: Individual vehicle controls are automated, such as electronic stability control or
automatic braking.
Level 2: At least two controls can be automated in unison, such as adaptive cruise control in
combination with lane keeping.
Level 3: The driver can fully cede control of all safety-critical functions in certain
conditions. The car senses when conditions require the driver to retake control and provides
a "sufficiently comfortable transition time" for the driver to do so.
Level 4: The vehicle performs all safety-critical functions for the entire trip, with the driver
not expected to control the vehicle at any time. As this vehicle would control all functions
from start to stop, including all parking functions, it could include unoccupied cars.
Potential advantages and disadvantages
Positive sides (+)
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Fewer traffic collisions, due to an autonomous system's increased reliability and faster reaction time
compared to human drivers.
Increased roadway capacity and reduced traffic congestion (due to reduced need for safety gaps), and
the ability to better manage traffic flow.
Relief of vehicle occupants from driving and navigation chores. People can do their own things while
their vehicle drives.
Higher speed limit for autonomous cars. Since the car controls the environment, it can react faster
and control the situation drop speed or stop in case of need.
Removal of constraints on occupants' state – in an autonomous car, it would not matter if the
occupants were under age, over age, blind, distracted, intoxicated, or otherwise impaired. Car can be
controlled by voice and answer the driver as well, due this it can be controlled even then when
normally it was impossible.
Alleviation of parking scarcity, since most of the drivers try to park their car as close as possible to
their destination, cars could drop off passengers, park far away where space is not scarce, and return
as needed to pick up passengers.
Overnight travel would let people sleep and arrive rested. Off course the overnight driving would be
safer, speed will be reduced so that lesser even more the dangerous situations.
Elimination of redundant passengers – humans are not required to take the car anywhere, as the
robotic car can drive independently to wherever it is required, such as to pick up passengers or to go
in for maintenance or delivering goods, mail services. This would be especially relevant to trucks,
taxis and car-sharing services.
Reduction of space required for vehicle parking. The robot-car go along the algorithm, that demands
from it straight parking between the lines on ground, according to the rules – not less than 20sm
between the line and the wheel, making the parking more organized.
Reduction in the need for traffic police and vehicle insurance. Robot-cars cannot break the traffic
regulations on purpose, thus lowering the number of road accidents.
Reduction of physical road signage – autonomous cars could receive necessary communication
electronically (although physical signs may still be required for any human drivers).
Smoother ride. Car decides the speed, knowing the traffic information it can slow down or speed up
according to the current situation; it may ride even without any stop for the red light because of speed
accurate speed control.
Lesser fuel consumption. Due to smoother ride the car fuel consumption is lesser that with a human
driver.
Friendly for city economics. Clearing the streets off the traffic jams makes the city to lose less money
on regulating the traffic.
Negative sides (-)
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Liability for damage. In accidental situations it is hard to find who to blame. Was it the fault
of the driver, autonomous car software or maybe someone have hacked the car
Resistance for individuals to forfeit control of their cars. Some people like to control their
vehicle, others, scared of robots, and don’t believe them.
Software reliability. We all know that in some cases our computers can lag, or a bug can
occur. What if something similar happen to a car, it could lead to serious injuries?
Cyber Security: A car's computer could potentially be compromised, as could a
communication system between cars.
Establishment of government regulations for self-driving cars. Currently only four states in
the U.S. have gave right for public road testing of autonomous cars.
Reliance on autonomous drive produces less experienced drivers for when manual drive is
needed.
Loss of driver-related jobs. Reduced demand for parking services and for accident related
services (Emergency rooms, Injury Lawyers, collision repair, etc.) assuming increased
vehicle safety. Reduction in jobs relating to auto insurance and traffic police.
Loss of privacy. One of the main features of these cars is connection to the Internet and
social networks. By this the car gets the information about its user that is personal
information that may be used against its owner.
Autonomous cars relying on lane markings cannot decipher faded, missing, or incorrect lane
markings. Markings covered in snow, or old lane markings left visible can hinder
autonomous cars ability to stay in lane.
Temporary construction zones which are not posted to any maps or data bases.
Determination of the severity of traffic lane obstacles, as in the question of safely straddling
a pothole or debris.
Increases costs. Requires additional vehicle equipment, service and maintenance, and
possibly additional roadway infrastructure.
Estimated Costs
Autonomous vehicle costs are uncertain. They require a variety of special equipment, including
sensors, computers and controls, which currently really expensive but are likely to become cheaper
with mass production. However, because system failures could be fatal to both vehicle occupants
and other road users, all critical components will need to meet high manufacturing, installation,
repair, testing and maintenance standards, similar to aircraft components, and so will probably be
relatively expensive. Autonomous vehicle operation may require subscriptions to special navigation
and mapping services. Other, simpler technologies add hundreds of dollars to vehicle retail prices.
For example, optional rearview cameras, GPS and telecommunications systems, and automatic
transmissions typically cost €500 to €2,000 extra. Autonomous vehicles require these plus other
equipment and services. Manufacturers will need to recover costs of development, ongoing service
(special mapping and software upgrades) and liability, plus earn profits. This suggests that when the
technology is mature, self-driving capability will probably add several thousand euros to vehicle
purchase prices, plus a few hundred euros in annual maintenance and service costs, increasing
annualized costs €1,000 to €3,000 per vehicle. These incremental costs may be partly offset by fuel
and insurance savings. Motorists spend on average approximately €2,000 for fuel and €1,000 for
insurance per vehicle-year. If autonomous vehicles reduce fuel consumption by 10% and insurance
costs by 30%, the total annual savings will average €500, which will not fully offset predicted
incremental annual costs.
Autonomous Vehicle Equipment and Service Requirements
 Automatic transmissions.
 Diverse and redundant sensors (optical, infrared, radar, ultrasonic and laser) capable of
operating in diverse conditions (rain, snow, unpaved roads, tunnels, etc.).
 Wireless networks. Short range systems for vehicle-to-vehicle communications, and longrange systems to access to maps, software upgrades, road condition reports, and emergency
messages.
 Navigation, including GPS systems and special maps.
 Automated controls (steering, braking, signals, etc.)
 Servers, software and power supplies with high reliability standards.
 Additional testing, maintenance and repair costs for critical components, such as automated
testing and cleaning of sensors.
First driverless car
First time driverless cars have been built in 1920-1930s. Those car weren’t autonomous those were
cars controlled by radio signals, just like toy cars. First time Achen Motor, a distributor of cars in
Milwaukee and surrounding territory, used Francis' invention under the name "Phantom Auto" and
demonstrated it in December 1926 at the streets of Milwaukee. The “Phantom Auto” was first
behind it was going second car with the “driver” who controlled the first car with radio signals.
Signals were caught by the transmitting antennae. The antennae introduced the signals to circuitbreakers which operated small
electric motors that directed
every movement of the car.
Next were cars powered by
circuits embedded in the
roadway and controlled by
radio, introduced in year 1939.
After this a series of tests were
made with circuits buried to
the roadway.
In 1953, RCA Labs
Image 1: This is how illustrated the driverless cars in 1920s
successfully built a miniature car that was guided and controlled by wires that were laid in a pattern
on a laboratory floor. In 1958, a full size system was successfully demonstrated by RCA Labs and
the State of Nebraska on a 400-foot strip of public highway just outside Lincoln, Neb. A series of
experimental detector circuits buried in the pavement were a series of lights along the edge of the
road. The detector circuits were able to send impulses to guide the car and determine the presence
and velocity of any metallic vehicle on its surface. It was developed in collaboration with General
Motors, who paired two standard models with equipment consisting of special radio receivers and
audible and visual warning devices that were able to simulate automatic steering, accelerating and
break control.
Next were in 1960, Ohio State University's Communication and Control Systems Laboratory
launched a project to develop driverless cars which were activated by electronic devices imbedded
in the roadway.
In the 1980s were made first cars that used laser radar, computer vision and autonomous robotic
control to direct a robotic vehicle at speeds of up to 19 miles per hour (31 km/h). In 1987, HRL
Laboratories (formerly Hughes Research Labs) demonstrated the first off-road map and sensorbased autonomous navigation.
The next generation vehicles
After 1990s making a robot car spread worldwide. Their own autonomous cars have been made in
U.S.A., Germany, U.K., Italy, and Japan. Those cars were using latest technologies: saccadic
computer vision, transputers, neural networks to control the steering wheel, lane control, stereoscopic vision.
The US Government funded three military efforts known as Demo I (US Army), Demo II
(DARPA), and Demo III (US Army). Demo III (2001) demonstrated the ability of unmanned ground
vehicles to navigate miles of difficult off-road terrain, avoiding obstacles such as rocks and trees.
James Albus at the National Institute for Standards and Technology provided the Real-Time Control
System which is a hierarchical control system. Not only were individual vehicles controlled (e.g.
throttle, steering, and brake), but groups of vehicles had their movements automatically coordinated
in response to high level goals.
The ParkShuttle, a driverless public road transport system, became operational in the Netherlands in
the early 2000s.
Autonomous vehicles have also been used in mining. Since December 2008, Rio Tinto Alcan has
been testing the Komatsu Autonomous Haulage System – the world's first commercial autonomous
mining haulage system – in the Pilbara iron ore mine in Western Australia. Rio Tinto has reported
benefits in health, safety, and productivity. In November 2011, Rio Tinto signed a deal to greatly
expand its fleet of driverless trucks. Other autonomous mining systems include Sandvik Automine's
underground loaders and Caterpillar Inc.'s autonomous hauling.
In the last five years a great progress were made in making an autonomous car. The major automotive
manufacturers, including General Motors, Ford, Mercedes Benz, Volkswagen, Audi, Nissan, Toyota, BMW,
and Volvo, are testing driverless car systems; some of them are really successful. For example Volvo started
their project Drive me car, driving on public roads. These cars can be already seen on the streets of Swedish
city of Goteborg. By the year 2017 this cars
will be 100.
In January 2014, Induct Technology's Navia
shuttle became the first self-driving vehicle
to be available for commercial sale. Limited
to 12.5 miles per hour (20.1 km/h), the
open-air electric vehicle resembles a golf
cart and seats up to eight people. It is
intended to shuttle people around
"pedestrianized city centers, large industrial
sites, airports, theme parks, university
campuses or hospital complexes.
Right now you can go to car reseller and a
Image 2: Navia the first commercial driverless car
get a car that have autonomous features.
Daimler’s Mercedes is leading the way with an add-on called “Stop & Go Pilot” available in its €79,800
flagship S-Class sedan. Backed by an array of 12 ultrasonic detectors, 5 cameras, and 6 radar sensors, the SClass can match the speed of the car in front of it in heavy traffic, even coming to a complete stop and
adjusting steering to stay in the lane, as it slowly trails the car ahead. The optional feature costs €2,678 in
Germany, where it’s already available.
Image 3: MB optional feature that brings us closer to autonomous cars
Autumn 2011 the London Airport Heathrow announced that its starting to use autonomous 4 men busses, that
deliver passangers from parking to the terminal. Unlike the mini-metro that most big airports have, this
busses go not along the railroad but by the ordinary road. Rigth now there are 21 of this car working in the
airport. They develop speed up
to 40km/h, they are watched
over by master computer, it
controlls that the busses wont
consintrated in one place.
Busses are absolutely free for
airoprt visitors.
Image 4: London Heathrow first started using autonomous busses
Google driverless car
The most popular of all autonomous cars is Google driverless car. It is the first car
that was allowed to be tested on public roads. It has a special license plate: red plate
with infinity sign ∞.
First of all Google car is not a new brand. Google car is a name of project to make a
software, called by the way The Google Chauffeur, Google uses 3 different brand. The main and most
common is Toyota Prius 6 total, one Audi TT and three Lexus RX450h.
All tests are accompanied in the driver's seat by one of a dozen drivers with unblemished driving records and
in the passenger seat by one of Google's engineers. The car has traversed San Francisco's Lombard Street,
famed for its steep hairpin turns and through city traffic. The vehicles have driven over the Golden Gate
Bridge and around Lake Tahoe. The system drives at the speed limit it has stored on its maps and maintains
its distance from other vehicles using its system of sensors. The system provides an override that allows a
human driver to take control of the car by stepping on the brake or turning the wheel, similar to cruise control
systems already found in many cars today. In April 2014, the team announced that their vehicles have now
logged nearly 700,000 autonomous miles (1.1 million km).
Google's robotic cars have about $150,000 in equipment including a $70,000 64-beam LIDAR (laser
radar) system by Velodyne. Lidar (also written LIDAR or LiDAR) is a remote sensing technology
that measures distance by illuminating a target with a laser and analyzing the reflected light. It is
mounted on the top of the car. This laser allows the vehicle to generate a detailed 3D map of its
environment. The car then takes these generated maps and combines them with high-resolution
maps of the world, producing different types of data models that allow it to drive itself.
Image 5: This is how Google Car see
The car has cameras fitted inside it which take pictures of surrounding and supply them to internal
computer to detect any obstacles in its way to read road signs and road data.
Image 6: Google car (Toyota Prius) devices
The biggest obstacle that Google car facing is that it mainly rest on high-definitional map of the
Earth’s surface, without this car won’t be able to maintain its location, but with ordinary maps it is
unreachable, due to ordinary maps can make an error of its location in meters, what can become
really dangerous. Because of this the driver must run the route for the first time, so that the lidar
made a clear picture and a really accurate map. After that Google car can drive by the route
absolutely autonomous.
The laser can differentiate between other cars, pedestrians, cyclists, and small and large stationary
objects, and it doesn't need light to be able to function. The radar arrays keep an eye any fastmoving objects from farther out than the laser can detect. The front-mounted camera handles all
traffic controls, observing road signs and stop lights for the same information that a human driver
uses. Google's computers combine data from the laser and the camera to create a rudimentary 3D
model of the immediate area, noting for example the color of an active traffic light.
There's a staggering amount of contextual software at work at all times. For managing lane changes,
there's an algorithm determining the smoothest route through the surrounding road combining
trajectory, speed and the safest distance from obstacles. When coming to an intersection without a
traffic light, Google's cars yield the right of way according to traffic laws. But if other drivers don't
take their appropriate turns, the Google car moves forward slightly, then watches for a reaction. If it
determines that the other driver still won't move, it takes the initiative.
The car can automatically park it. It scans RFID tags and QR codes printed on road to detect its
parking spot. QR codes printed on the road also help the car to detect its current location. The QR
codes and RFID tags contains location information with exact coordinates.
Today automotive systems
Today major automotive brands can offer you some of the newest technological devices. Those
systems are . I will explain how they work and what they do.
Advanced front-lighting system (AFS)
In 2000s was established an idea of moving or optimizing the headlight beam in response not only to
vehicular steering and suspension dynamics, but also to ambient weather and visibility conditions,
vehicle speed, and road curvature and contour. A task force under the EUREKA organization,
composed primarily of European automakers, lighting companies and regulators began working to
develop design and performance specifications for what is known as Adaptive Front-Lighting
Systems, commonly AFS. Rather than the mechanical linkages employed in earlier directionalheadlamp systems, AFS relies on electronic sensors, transducers and actuators. Other AFS
techniques include special auxiliary optical systems within a vehicle's headlamp housings. These
auxiliary systems may be switched on and off as the vehicle and operating conditions call for light
or darkness at the angles covered by the beam the auxiliary optics produce. A typical system
measures steering angle and vehicle speed to swivel the headlamps. The most advanced AFS
systems use GPS signals to anticipate changes in road curvature, rather than simply reacting to them.
Blind spot monitor
A blind spot monitor is a vehicle-based sensor device that detects other vehicles located to the
driver’s side and rear. Warnings can be visual, audible, vibrating or tactile.
However, blind spot monitors are an option that may include more than monitoring the sides of the
Image 7: Blind spot monitor
vehicle. It can include "Cross Traffic Alert," "which alerts drivers backing out of a parking space
when traffic is approaching from the sides. If side view mirrors are properly adjusted in a car, there
is no blind spot on the sides.
In 2007 Volvo developed a protection system BLIS. BLIS is an acronym for Blind
Spot Information System. System produced a visible alert when a car entered the blind spot while a
driver was switching lanes, using two door mounted lenses to check the blind spot area for an
impending collision.
In 2010, the Nissan Fuga/Infiniti M for the first time introduced a blind spot intervention system, it
not only signals the driver when there an obstacle on the blind spot but also can counter steer the
vehicle to keep it from colliding.
Lane departure warning system
Lane departure warning system is a technology designed to warn a driver when the vehicle begins to
move out of its lane (unless a turn signal is on in that direction). These systems are designed to
minimize accidents by addressing the main causes of collisions: driver error, distractions and
drowsiness.
There are two main types of systems:
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Systems which warn the driver (lane departure warning, LDW) if the vehicle is leaving its lane
(visual, audible, and/or vibration warnings)
Systems which warn the driver and, if no action is taken, automatically take steps to ensure the
vehicle stays in its lane (lane keeping system, LKS)
The first production lane departure warning system in Europe was developed by the United
States Company Iteris for Mercedes Actros commercial trucks. The system debuted in 2000, and is
now available on most trucks sold in Europe.
In both LDW and LKS systems, the driver is warned of unintentional lane departures by an
audible rumble strip sound generated on the side of the vehicle drifting out of the lane. No warnings
are generated if, before crossing the lane, an active turn
signal is given by the driver
Lane warning/keeping systems are based on:
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Video sensors in the visual domain (mounted behind
the windshield, typically integrated beside the rear
Image 8: Lane departure warning system
mirror)
Laser sensors (mounted on the front of the vehicle)
Infrared sensors (mounted either behind the windshield or under the vehicle
Lane Keeping Assist is a feature that in addition to Lane Departure Warning System automatically
takes steps to ensure the vehicle stays in its lane. LDW and LKS have one major negative side; they
rely on visible lane markings. If the lane is faded, missing, either incorrect or markings covered in
snow or old make the system work incorrectly.
Collision avoidance system
A collision avoidance system is an automobile safety system designed to reduce the severity of an
accident. Also known as precrash system, forward collision warning system or collision mitigating
system, it uses radar and sometimes laser and camera sensors to detect an imminent crash. Once the
detection is done, these systems either provide a warning to the driver when there is an imminent
collision or take action autonomously without any driver input (by braking or steering or both)
Advanced Automatic Collision Notification
Advanced Automatic Collision Notification (AACN) is also known as Advanced Automatic Crash
Notification and is the successor to Automatic Collision Notification (ACN). To develop procedures
that will help emergency medical responders better and more quickly determine if a motorist needs
care at a trauma center after a vehicle crash, Center for Disease Control (CDC) conducted a vehicle
telematics initiative to develop evidence-based protocols for the emergency medical community to
effectively use automotive telemetry data. By enabling responders to more quickly identify,
diagnose, and treat injuries, these data will help to reduce death and injuries among vehicle crash
victims. As part of this initiative, CDC convened a panel of emergency medical physicians, trauma
surgeons, public safety, and vehicle safety experts. The panel considered how real-time crash data
from the advanced automatic crash notification (AACN) vehicle telematics system and similar
systems can be used to determine whether injured patients need care at a trauma center. By using a
collection of sensors, vehicle telemetry systems like AACN send crash data to an advisor if a vehicle
is involved in a moderate or severe front, rear, or side-impact crash. Depending on the type of
system, the data include information about crash severity, the direction of impact, air bag
deployment, multiple impacts, and rollovers (if equipped with appropriate sensors). Advisors can
relay this information to emergency dispatchers, helping them to quickly determine the appropriate
combination of emergency personnel, equipment, and medical facilities.
The Vehicular Emergency Data Set is an XML-based standard for reporting collision data elements
and medical data elements related to a collision. The standard was developed by the ComCARE
Alliance, and is aimed at relaying critical information to facilitate efficient emergency response.
This data set can be transmitted automatically to a response center, which can then forward it to
emergency services providers.
Automotive night vision
An automotive night vision system is a system that allows driver to see in dark conditions when
headlights aren’t enough for lightening humans vision. There are two types of night vision system
active and passive.
Active systems use an infrared
light source built into the car to
illuminate the road ahead with
light that is invisible to humans.
There are two kinds of active
systems: gated and non-gated. The
gated system uses a pulsed light
source and a synchronized camera
that enable long ranges (250m)
and high performance in rain and
snow.
Image 9: ANV projects the vision on the panel
Passive systems do not use an
infrared light source, instead they capture thermal radiation already emitted by the objects, using
a thermo graphic camera.
There are three ways of displaying the nigh vision image.
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instrument cluster using a high resolution liquid-crystal display (LCD), newest type
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navigation system or information screen, least expensive and with display's location further
away from driver's field of vision (used exclusively by BMW, and theW212 E-class)
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windshield via head-up display, earliest type, dimmer knob can reduce brightness, display
nearest to driver's line of sight
Automatic parking
Automatic parking is a system that uses vehicle sensors, such as sonar, cameras or radar eventually
using all of this the car will detect the parking space size and distance from the roadside, then drive
the car into the parking space. If the size of parking slot is enough car parks itself. Parking starts
when the driver stops the vehicle according to the parking slot, then he chooses what kind of parking
driver wants to be made.
Traffic Sign Recognition
Traffic Sign Recognition is a technology by which a vehicle is able to recognize the traffic signs put
on the road e.g. "speed limit" or "children" or "turn ahead".
These first TSR systems which recognize speed limits were developed in cooperation
by Mobileye and Continental AG. They first appeared in late 2008 on the redesigned BMW 7Series, and the following year on the Mercedes-Benz S-Class. Currently these systems only detect
the round speed limit signs found all across Europe (e.g.). Second generation systems can also detect
overtaking restrictions.
Driver Monitoring System
Driver Monitoring System, also known as Driver Attention Monitor, is a vehicle safety system first
introduced by Toyota in 2006 for its and Lexus latest models. It was first offered on the GS 450h.
The system's functions co-operate with the Pre-Collision System (PCS). The system uses infrared
sensors to monitor driver attentiveness. Specifically, the Driver Monitoring System includes
a CCD camera placed on the steering column which is capable of eye tracking, via infrared
LED detectors. If the driver is not paying attention to the road ahead and a dangerous situation is
detected, the system will warn the driver by flashing lights, warning sounds. If no action is taken,
the vehicle will apply the brakes (a warning alarm will sound followed by a brief automatic
application of the braking system). This system is said to be the first of its kind.
In 2008, the Toyota Crown system went further and can detect if the driver is becoming sleepy by
monitoring the eyelids.
Autonomous cruise control system
Autonomous cruise control (also called adaptive or
radar cruise control) is an optional cruise control
system for road vehicles that automatically adjusts Image 10: ACC layout
the vehicle speed to maintain a safe distance from
vehicles ahead. It makes no use of satellite or roadside infrastructures or of any cooperative support
from other vehicles. Hence control is imposed based on sensor information from on-board sensors
only. The extension to cooperative cruise control requires either fixed infrastructure as with
satellites, roadside beacons or mobile infrastructures as reflectors or transmitters on the back of
other vehicles ahead.
Such systems go under many different trade names according to the manufacturer. These systems
use either a radar or laser sensor setup allowing the vehicle to slow when approaching another
vehicle ahead and accelerate again to the preset speed when traffic allows. ACC technology is
widely regarded as a key component of any future generations of intelligent cars. The impact is
equally on driver safety as on economizing capacity of roads by adjusting the distance between
vehicles according to the conditions.
Laser-based ACC systems do not detect and track vehicles in bad weather conditions nor do they
reliably track extremely dirty (non-reflective) vehicles. Laser-based sensors must be exposed, the
sensor (a fairly large black box) is typically found in the lower grille offset to one side of the
vehicle.
Radar-based sensors can be hidden behind plastic fascias;
however, the fascias may look different from a vehicle without
the feature. Single radar systems are the most common.
Systems involving multiple sensors use either two similar
hardware sensors or one central long range radar coupled with
two short radar sensors placed on the corners of the vehicle.
GPS-aided ACC: the GPS navigation system provides guidance
input to the ACC. On the motorway, the car in the front is
slowing down, but with turn signal on and it is actually heading
for a highway off-ramp. A conventional ACC would sense the
car in front was decelerating and it would simply apply brakes
accordingly. But with GPS-guided ACC takes into account the
Image 11: Jeep’s front ACC radar
approaching highway exit and it simultaneously receives images from a camera attached e.g. behind
the front pane to the rearview mirror. The camera may detect the turn signal from the car ahead. So
instead of braking, this new system continues uninterrupted, because it knows that the car in front
will exit the lane.
GPS-aided autonomous cruise control system design scheme
This scheme describes how GPS-aided ACC system works.
First of all when driver gets into a full traffic he activates the ACC system. System starts reading
speed from the front car. If the traffic changed to normal, there isn’t any front car or front car got out
of range, then the system asks the driver to shut it down. If the traffic didn’t change, system analyzes
the front cars speed.
If the speed increased, the system increase the cars speed, if it doesn’t exceeds the speed limit.
When the front car speed decreases, system checks using the front mounted camera, if there is a
turning signal on, system uses GPS navigation to analyze the current road situation. If according to
the GPS car leaves the lane or approaching highway exit, system doesn’t change the speed, but allows the
car to change the distance. After the front car leaves, the system returns to its initial position, scanning the
front car speed. When happens that the front cars turn signal isn’t on, system slows down the car,
maintaining the distance, and after that system returns to its initial position.
Autonomous car working scheme
In near future, driving would look something like described above on the scheme. You start your
car, after that you can activate the autopilot system. Next step is that you enter GPS coordinates.
GPS gives you available routes. If they suites you chose one of them. Car starts to leave the parking,
using cameras, sonar and laser sensors. May occur that automatic can’t leave the parking by its own,
system asks you to take over the control. If everything went all right and autopilot left the parking it
continues to go on the route. Many times on the road happens dangerous situations like, some road
accidents, repairs or any other thing that may disturb the driving. When autopilot detects these
things, it analyzes the situation and if it can, it proceeds with driving otherwise it stops the car and
asks the driver to take over the control.
Comparison of efficiency
Here I tried to make a visual example of comparison of efficiency. I made a table where are
compared the driving, in the city by straight without turns, of the ordinary (with driver car) and
autonomous car.
With driver car
Autonomous car
Acceleration up to 50 km/h
Acceleration up to 50 km/h
Stop on the red light
Analyzing the situation
Acceleration up to 50 km/h
Smooth breaking
Smooth Acceleration
With driver car accelerates, if driver sees red light he stops. Normally 70-80% of drivers don’t
predict their route, they make absolute stop on the red light. After that they accelerate up to 50km/h.
As it known as more sharply you speed up and slow down, the more fuel car consumes. Driverless
car always tries to predict the traffic conditions ahead, using cameras, GPS and other systems to
detect traffic light. Detecting this driverless car decrease speed lesser allowing the car to pass the
traffic light without stopping. This makes the driving smoothly. That is why autonomous car
consumes lesser fuel.
60
50
40
Normal car
30
Autonomous car
20
10
0
0
1.stage
2.stage
3.stage
4.stage
The graphic above shows that normal car driving is more sharply then autonomous. The data at the
left is speed, below stages. First stage is acceleration, second stage is slowing down for red light,
third stage is acceleration and fourth stage is slowing down for red light.
SWOT analysis of autonomous car
Internal origin
Helpful
Harmful

Safer, because of special precrash
systems.



Lesser fuel consumption.
Removal of constraints on occupants'
state.
Relief of vehicle occupants from
driving and navigation chores.




In accidental situations it is hard to
find who to blame.
Resistance for individuals to forfeit
control of their cars.
Software reliability.
Establishment of government
regulations for self-driving cars.
External origin



Cities become without traffic jams
Accidents become real rarity
Humans can absolutely take care
of their things while car drives.


Software errors, bugs, lags
Unexpected dangers on road(traffic
collisions, road breakings)
Future perspective and capabilities of autonomous car
To date, many companies engaged in the development of autonomous cars. Some companies (like
Google) are developing an independent system for vehicles, which can be installed in any car .
Other companies (like Mercedes-benz) create a completely new automatic car. Both approaches
have their pros and cons. The first option has the main advantage is that this system can purchase
any car company and installed in their car. The second option is good in that car system is created
not only in software but also on the hardware level, thereby car designed to allow systems to be
introduced into it. The main problems of all existing systems of autonomous cars now is that they
have not yet fully autonomous to travel themselves on the road without a driver. They must have at
least be familiar with the route.
Like many similar systems, automatic machines, with the increasing number of these vehicles,
creating the so-called collective intelligence. The vehicles will contact each other, gathering
information, thus creating the road picture that will be clearer, cars will know in advance the
situation on the road.
For best performance, it is also desirable for autonomous cars intelligent road system. The road
system consists of surveillance cameras that monitor the overall situation on the road, from laser
sensors that control the distance between the cars and their speed. Placed along the road tables that
notify drivers, passengers have to be more precise, about the changes on the road. Computer receive
the information gathered from surveillance cameras and sensors.
In the future, the car will only receive commands from its driver. The driver will leave the house in
advance, using his phone, calling his own car right to the door. Get in the car and say to the onboard
computer the destination. Moreover in weekdays, having access to the calendar and knowing the
standard schedule of its owner, the machine can immediately start moving along the route without
waiting for its owner any orders. On the way to the end point of the route, the vehicle driver can use
the information, such as social networking, offering along the way, for example, to take a turn to
restaurant, which the driver Like’ed last time. Upon arrival at the destination, the driver leaves the
car, and the car itself goes to the parking lot and parks itself.
Conclusion
In our time, the car is no longer a luxury but a means of transportation. Therefore, it is necessary
that the car was safe, economical and accessible. Autonomous cars - this is what is able to solve all
these problems. Because automatic cars are able to do this. Automatic cars full of different systems
that can reduce the risk of accidents or to decrease the impacts. A significant advantage of
autonomous cars is their efficiency. Because the computer is able to more thoroughly analyze the
situation, the car goes more smoothly and, therefore, more economical. And of course autonomous
cars can allow people to who movement by private transport was closed before, have a car for them
self and drive it without any help. Of course, at this point all this is far from ideal, but the
technology is evolving incredibly fast. Prices for all of these technologies are also have reduced in
the past few years, so maybe soon on our cities we shall see driverless car driving around. And at the
end I would like to present a popular legend:
It is said that Bill Gates once compared computers with automobiles and concluded, “If GM had
kept up with the technology like the computer industry, we would be driving $25 cars that got 1,000
miles to the gallon.”
In response, according to the legend, General Motors issued the following press release. If General
Motors developed technology like Microsoft, motor vehicles would have the following
characteristics:
 Automobiles would frequently crash for no apparent reason. This would be so common that
motorists would simply accept it, restart their car and continue driving.
 Occasionally, for no reason, all doors would lock, and motorists could only enter their
vehicle by simultaneously lifting the door handle, turning the key, and holding the radio
antenna.
 Vehicles would occasionally shut down completely and refuse to restart, requiring motorists
to reinstall their engine.
 Every time GM introduced a new model, car buyers would have to relearn to drive because
all controls would operate in a new manner.
 Whenever roadway lines are repainted motorists would need to purchase a new car that
accommodates the new “operating system.”
 Cars could normally carry only one passenger unless the driver paid extra for a multipassenger license.
 Apple would make a car powered by the sun, more reliable, five times as fast, that required
half the effort to drive, but could operate on just five per cent of roads.
 Oil, water temperature and alternator warning lights would be replaced by a single 'general
car default' warning light.
 Airbags would ask, 'Are you sure?' before deployment.
 Vehicle buyers would be required to also purchase a set of deluxe road maps from RandMcNally (a GM subsidiary), regardless of whether or not they want it. A trained mechanic
would be required to delete them from the glove compartment.
 To shut off the engine drivers would press the 'start' button.