Road Traffic Efficiency and Safety Improvements Trends
Vadim Glazunov
1
, Leonid Kurochkin
1
, Mihail Kurochkin
1
, Sergey Popov
1
and Dimitri Timofeev
2
1
Telematics department, Saint-Petersburg State Polytechnic University, St. Petersburg, Russia
2
Distributed Computing and Networking department, Saint-Petersburg State Polytechnic University, St. Petersburg, Russia
Keywords: Unmanned Vehicle, Traffic Management, Human Factor, Traffic Regulations, Reducing Accidents, Driver
Aids, Crash Avoidance, Driver Assistance, Vehicle Safety Systems.
Abstract: Given article covers the next few problems: safety in highway traffic management; electronic assistance in
conventional transportation; cooperative movement of conventional vehicles and driverless cars; some of
the unmanned vehicle technologies.
1 INTRODUCTION
Road traffic efficiency and safety remains an actual
task of the automotive industry and road services.
The challenge of reducing the costs of
transportation, decreasing negative environmental
impact of the roads, minimizing road accidents,
developing network of customer care and support
services are closely related. These issues get
comprehensive solutions provided by vehicle
manufacturing companies, by state and regional road
traffic organizations and regulation bodies.
Traditionally, vehicle manufacturing companies test
their models using criteria such as: adult passengers’
safety protection, children passengers’ safety
protection, safety protection of pedestrians and
availability of the safety systems in the car. Rating
of each car model shows how successfully certain
technical solutions incorporated into a design of a
car have manifested themselves.
Modern automobile technologies offer two
pathways to achieve the main goal – efficient and
safe driving conditions. The first way offers driver
assistance facilities, while the other proposes
elimination of the “human factor” in context of
driving functions by replacing him with robot.
1.1 Crash Avoidance and Driver
Assistance Systems
The primary target for creating this class of
electronics and automatics is to help driver to make
right decision in difficult road situations, warn him
about possible appearance of such incidents and also
eliminate some of the weak points like human
reaction time, concentration and attention. Described
below are some of the driver’s aids with few
valuable additions.
1.2 Blind Spots Monitoring System
If there is a faster car approaching from behind and
at some point it gets into blind spot to the left or
right behind the vehicle, a warning light starts
twinkle in the external mirror. The first to introduce
a similar electronics in their cars was Volvo
company and now it is put on cars of different
brands. But Mazda has been able to develop the
idea. First, the system is not only able to engage the
warning lights in the side mirrors when there is a car
in the blind spot, but also to predict the behavior of
vehicles approaching from behind. Computer
monitors the area of 50 m behind the car and if the
faster car approaches, the indicator lights up 5
seconds before the latter will appear in dangerous
proximity. Secondly, electronic assistant starts
beeping when the driver engaged the turn signal
when there's another car close enough on the
adjacent lane (Mazda.com, 2013).
Today, only onboard computing resources and
sensors are used within technology, but its abilities
can be significantly extended after integration with
positioning system and communication modules. In
a automotive mesh network vehicles could exchange
data about obstacles in blind spots of each other,
thus improving safety of road maneuvers in very
difficult traffic conditions.
439
Glazunov V., Kurochkin L., Kurochkin M., Popov S. and Timofeev D..
Road Traffic Efficiency and Safety Improvements Trends.
DOI: 10.5220/0004589504390446
In Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO-2013), pages 439-446
ISBN: 978-989-8565-71-6
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
1.3 Night Vision Camera
Such equipment is often found on the German car
models, although the first to implement this kind of
technology was Cadillac. 2000 DeVille was first
production car equipped with the infrared night-
vision camera. Picture is transmitted to the display in
the dashboard and additional information and icons
are projected on the windshield. The fact is that the
original image coming from an infrared camera is
quite specific and difficult to perceive by human
eyes. Therefore, Audi engineers decided to use a
special unit that processes image in their vehicles. It
paints an image so that the driver could clearly
distinguish important information such as
pedestrians which are sometimes visible only at the
last moment before accident. Most interesting is that
night vision systems are able to distinguish between
people on the sidelines (not dangerous) and
emphasizes those who come to the roadway. People
on the road are shown in red as opposed to "safe"
green pedestrians at the roadside. The system is able
to recognize people from a distance of up to 100 m.
Moreover, the camera adjusts to the lighting
conditions and the processor ensures that other warm
objects (street lights, car headlights) do not "pollute"
the picture with excessive light (Audi.com, 2013).
Adding communicative abilities to such system
will drastically improve pedestrian safety at night by
sending coordinates and speed of the obstacles from
one car to others in range so that their drivers know
about possible danger in advance.
1.4 Traffic Sign Detection
Traffic sign recognition is a driver support function
which can be used to notify and warn the driver
which restrictions may be effective on the current
stretch of road. Examples for such regulations are
speed limit zones or "no-overtaking" indications.
The system can help the driver to maintain a legal
speed, obey local traffic instructions, or urban
restrictions. It is also able to recognize country
specific signs.
One of the developers of such technology is
Mobileye, whose system is available from 2008 on
the BMW 7-series. The system uses camera-based
object recognition and can be developed to compare
the data with those coming from digital maps of a
navigation system and traffic services. This will
offer additional system robustness, especially in
cases where the vision system cannot provide the
needed information, such entering urban areas which
are not marked by traffic signs. With a VGA
resolution imager the system can provide reliable
detection for targets with a lateral distance of 10 m,
a vertical distance of 7 m and at vehicle speeds of up
to 250kph. This provides the current system with a
very high performance even in challenging high
speed situations on multi lane highways. As high
resolution sensors become available for automotive
use, there will be abilities to increase the effective
detection range, as well as detecting more “context”
and iconic information (Mobileye.com, 2013).
1.5 Lane-Keeping System
Even some reasonably priced cars like Opel Astra
and Ford Focus have already received equipment
which monitors the road marking and control the car
so that it is always kept in its lane. Usually, system
scans the road with a video camera at the top of the
windshield but then different brands of this feature
work a bit different. Infiniti’s electronics begins to
slow down left or right wheel slightly to steer the car
to the center of the lane. Ford uses electric power-
steering mechanism; furthermore if the car is going
out of lane without enabling turn signals, the
steering wheel vibrate. All manufacturers of the
system at the same time give the warning sounds and
light the corresponding icon on the dashboard
(Media.ford.com, 2013).
System can be enhanced with usage of
communication capabilities and navigation
functions. When installed on a large amount of cars,
lane-keeping system can collect data about road
marking and send it bundled with geographic
coordinates and timestamps to a dedicated cloud
service. This allows creating very detailed lane-
based road maps in a brief time. Maps will be
updated automatically using data collected from
vehicle on a daily or weekly basis.
1.6 Automatic Emergency Braking
Automatic braking is a car technology that “senses”
an imminent collision with another vehicle, person
or obstacle and responds by applying the brakes to
slow down the vehicle without any driver
participation. One of the currently available in
production cars is Mercedes-Benz' Pre-Safe Brake
system. It constantly monitors the area in front of the
car and activates warning sound and light signals for
the driver if the distance to the obstacle ahead
shrinks so fast, that according to the computer’s
calculations a collision will occur in 2.6 sec. If at
this point the driver starts braking, but according to
the calculations slowing down isn't enough, then it
ICINCO2013-10thInternationalConferenceonInformaticsinControl,AutomationandRobotics
440
will automatically increase the braking force. If the
driver doesn’t use brakes at all, then brakes will be
applied automatically at the time of 1.6 seconds
before the collision. Initially, electronics doesn’t use
brakes at 100% of braking force, giving the driver an
opportunity to decide to drive around obstacles. But
in 0.6 seconds before impact the brakes will
automatically go to the maximum (Euroncap.com,
2010).
Using such systems to prevent crashes is
problematic, so practical systems are often snap into
action only to reduce crash speed in some situations.
Sensors used to detect other vehicles or obstacles
can include radar, video, infrared, ultrasonic or other
technologies. GPS sensors can detect fixed dangers
such as approaching stop signs through a location
database. Such GPS-assisted system was announced
by Toyota (Mydigitallife.info, 2008).
1.7 Adaptive Cruise Control
This system is also known as Active cruise control.
It automatically adjusts the speed of the car to keep
safe distance behind the lead vehicle. The system
uses laser or radar to measure the distance to the
next car, it then relies on basic cruise control
features to accelerate or slow down the vehicle
according to changing gap between the cars.
Adaptive cruise control often includes a pre-crash
system, which warns the driver and provides brake
support if there is a high risk of collision
(Media.ford.com, 2012).
System can also be improved with
communication abilities and navigation services
integration for retrieving actual traffic information,
such as average speed on specific roads. Automotive
mesh network can be used to “tell” the following car
about maneuvers and speed changes on leading car.
Such systems are used in cars equipped with
autonomous driving systems.
1.8 Early Collision Preparation
Unfortunately, if the "electronic intelligence" has
realized that a collision is unavoidable it can't do
very much. In the last moments before crash seat
belts are tightened, seat bolsters are tightly wrapped
around the body (unless of course they are
adjustable), windows and sunroof are closed and if
there is a sliding monitor then it will be folded. To
some extent, these functions are now available in the
different car maker’s vehicles.
Again, one of the most advanced technology of
the time is Mercedes-Benz' Pre-Safe system.
Equipment of the latest generation, which was for
example the current E-Class, can even adjust the
front head restraints and cause rear seats to move to
the upright position because it reduces the risk of
sliding under the seat belt. Moreover, electronics
differently prepares for different types of accidents.
That is, for example, if there is a risk of a flip-over,
the windows and sunroof will be closed and in other
cases they will remain open. In that case it will be
easier to evacuate the victims. All of the actions
taken by Pre-Safe are reversible: if the collision is
avoided, tension is removed from the seat belts and
the occupants can readjust their seats
(Autoevolution.com, 2011).
1.9 Emergency Call
In case of a serious accident people’s life may
depend on delay between the crash and emergency
call. Medical assistance or fire brigade should arrive
to the required site as soon as possible. Electronic
assistant can instantly send SMS with the geographic
coordinates of the accident, the data on the impact
force (the nature of an accident and risk to humans
can be roughly determined by the activated airbags),
and the number of passengers. It also turns on the
speaker phone when connected with emergency
service operator. Call comes not to an ambulance or
the police, but on the vehicle brand’s own call
center. Experts will decide how to act according to
information they received from on-board systems
(Ford.co.uk, 2012).
Some of the above-considered systems and
technologies are already available on production
cars; others are on their way to commercial
realization. Most of the reviewed systems were
developed independently and by many different
equipment manufacturers. Therefore, there is no
standardization in protocols and interfaces used and
allowed by these products. One of the very
important tasks is integration of all of the onboard
computing resources and technologies into a
dedicated redundant computer with standard
interfaces, protocols and communication
capabilities. All of its functions could be
programmed in software using high-level
programming languages and almost unlimited set of
peripheral devices (sensors, cameras,
communication modules, etc.), which could be
plugged-in or upgraded to add new features and
improve system performance and reliability. This
should be done on a basis of open standards, which
allows any manufacturer to create its own solutions
and ensures equal access for all participants, such as
RoadTrafficEfficiencyandSafetyImprovementsTrends
441
car makers, device manufacturers, software
developers, regulatory authority, etc.
2 AUTONOMOUS CARS
OR PERSONAL AUTOMATED
VEHICLES
The design of unmanned vehicles equipped with
sensors and the necessary software should be
considered as a new way to increase safety. The
work in this direction is conducted by the major
companies such as Audi, Nissan, Toyota, Lexus,
Mercedes, Google, VOLVO and some others. The
most obvious advantages of unmanned vehicles is
increasing safety of vehicles and pedestrians. The
vast majority of the road accidents are caused by
human factors: fatigue, inattention, distracting
affairs, ignorance of the road traffic rules, slow
reaction, lack of the car driving experience in
emergency situations, lack of information of the
road conditions, and more (Census.gov, 2012).
The modern concept of an unmanned vehicle
envisages equipment of a vehicle by a sensor
system, technical facilities management units and AI
software.
The hardware and software system allows to get
the real time detailed model of a vehicle in motion
surrounding area, location of neighboring vehicles
and obstacles, presence of pedestrians, details of the
road markings, traffic lights and overall road traffic
characteristics. This data is further used to estimate
the traffic situation and to develop the controlling
signals on the vehicle aggregates (Robots.ox.ac.uk,
2012).
2.1 Advantages
Safety. Google developers claim that an autonomous
car driving system is able to process a lot more
information and to make decisions much faster than
a human driver can, by thus effectively protecting
passengers from road accidents. Besides that, thanks
to a high-sensitivity sensors, a car will be able to
"see" the objects in the dark (walking on the sides of
the road pedestrians or running across the road
animals) that are inaccessible to the human eye, and
to timely react on the road situation, slowing the car
speed down to the full stop (En.wikipedia.org,
2013).
Precise Compliance to the Traffic Rules.
Unlike the usual driver, unmanned vehicle will
never make a deliberate violation of the traffic rules.
If a computer system will treat the traffic situation as
potentially dangerous, it will take preventives
measures to avoid possible accidents, starting from
choosing the most optimal driving route up to a full
stop. In addition, broad usage of unmanned vehicles
will decrease traffic jams caused by drivers.
Comfort. The owner of an unmanned vehicle
may forget about such problems as searching for a
parking space - standalone car driving system will
find a free parking space in the final destination and
will park a car independently. Equipped by an
accurate information about the traffic in a given
point of the route, a "drone" will see in advance a
traffic jam, will evaluate its scope and will choose
an alternative route if needed.
2.2 Limitations
Reducing the posItioning Precision with
Worsening Weather Conditions. Changing
weather conditions affect the state/environment
characteristics, laser and radio signals, and have a
detrimental effect on the accuracy of radar systems
and sensors used to provide active safety systems for
manned vehicles, as well as unmanned ones, in
particular the ones designed by Google. The
reflecting ability of other objects is also affected by
the changing weather conditions reducing working
accuracy of active safety systems. Inaccurate
estimation of the road surface - icy or wet impedes a
proper automatic selection of the most suitable mode
of transmission and suspension systems settings.
Road Traffic Outside the Highways. The lion's
share of testing of unmanned vehicles is conducted
in megacities and on highways having high quality
road surface, road markings lines and lighting
devices. Research in automation of a car moving
over a rough terrain are getting active today, for
example, Google has recently announced of
inclusion of SUV Lexus in their unmanned vehicles
test park.
Legal Questions. To date, the existing
legislation systems of several developed countries
do not contain provisions for determining the
persons responsible for the accidents with unmanned
vehicles. This situation is seriously slowing down
the process of deploying and testing unmanned
vehicles in the real world traffic conditions
(Greencarcongress.com, 2011).
Accuracy of Electronic Maps. At the heart of
an unmanned car controlling system, for example
the one from Google are laying electronic maps with
panoramic objects views. The absence of such maps,
or having them out of date including the maps being
ICINCO2013-10thInternationalConferenceonInformaticsinControl,AutomationandRobotics
442
not in accordance with the season of year is a serious
barrier to the usage of unmanned vehicles.
Cost of the Test Sample. To date, the cost of the
test sample of Google unmanned vehicle is more
than 150 thousand dollars. The main cost (about
70,000 dollars) constitutes the usage of an optical
sensor LIDAR.
Dependence on a Navigation Signal Quality.
Usage of GPS or GLONASS systems to position
unmanned vehicles causes difficulties while
operating in tunnels, canyons and in other places
having unstable level of GPS or GLONASS signals
coverage.
In the dispute between the supporters and the
opponents of unmanned vehicles the formers’
position is more preferred because standalone
machine scans the surrounding area over a very
large radius (60-80 meters) and therefore the amount
of data, which is taken into account to make
solutions is much larger. This is a human-driver who
might miss a child suddenly popping-up on the road.
This is a human-driver who might linger and get
scared. This is a human-driver who would have at
least 0.5 seconds reaction to a sudden obstacle on
the road. This is a human-driver who regularly
exceeds the traffic speed.
A computer system does not have all the
mentioned above disadvantages, in a fraction of a
second and for many tens of meters, it will notice the
people running to or crossing the road, or standing
on the sidelines, and it will instantly make an
optimal decision. An autopilot will timely detect a
pedestrian moving quickly enough to get under the
car wheels, and then that autopilot will slow down
its car to predict the movement of this pedestrian and
to eventually eliminate accident.
If there are any objects on the road sidelines
hindering the view, an autopilot will slow down up
to a full stop to ensure there are no pedestrians
where they can appear provoking accidents.
An autopilot will react faster than a human in the
case of emergency and will handle the situation
using an optimal program. If an accident does occur
its consequences will be less severe. The car’s
computer will immediately notify emergency
services. Images from the cameras will instantly get
transferred on board and into the ambulance. All
these actions will reduce the time and will increase
the chances of the injured people. The computer will
record all the telemetry, and that records will
simplify the legal disputes.
Even if an accident would be caused by a fault of
a computer system the odds according to the overall
statistics are that such an accident would happen 10
times less frequently than when a car would be
driven by a human.
In the same time, the running nowadays polemics
of supporters and opponents of unmanned cars is
based on an objective contradiction, originating from
the fact that we are currently trying to combine an
informal system of movement of vehicles with a
formal one. The dominant of the former system is a
person (a car driver) while the dominant of the latter
is an unmanned vehicle system (actually a robot).
The person is weakly formalizable object, and the
robot is a machine, though endowed with some traits
of “intelligence”. Simultaneous participation of such
diverse entities in highways traffic does designate
the difficulties that the road traffic regulation
organizations are trying to resolve.
From the objective contradiction, we have
outlined above, follows the technical problem
associated with the collection of the road traffic data.
Currently, the entire set of technical systems
displaying information about a road situation
focuses on humans’ perception, their senses and
their ways of information gathering and processing.
The cars sensors capabilities could in some respects
be better, and in other respects - worse than the ones
of humans. In addition, humans always use their
experience and intuition, their ability to foresee the
situation, to analyze the behavior of the other
participants of the road traffic.
It is easy to assume that a cooperative
satisfaction of the requirements of the two systems
will lead to an increase of complexity of the traffic
control systems and to the growth of negative ratings
of the practical usage of unmanned vehicles (first of
all by the undisciplined drivers).
The objective contradiction is possible to be
resolved in two ways:
1. Developing regulations on driving unmanned
vehicles on dedicated lines or highways only: in
this case a new model of the road traffic control
is created, new requirements for the operational
information gathering systems is developed, new
protocols of communication between vehicles
and maintenance services and a set of documents
determining legal responsibilities of the road
traffic participants and regulators are elaborated.
Detailed development and implementation of this
option will solve the main problems of the road
transportation organization - reducing accidents,
reducing costs, improving the environment.
2. The organization of the group traffic of
unmanned vehicles with one or more driver-
instructors: in this case the road traffic rules have
to be revised considering particular properties of
RoadTrafficEfficiencyandSafetyImprovementsTrends
443
the group traffic of vehicles (crossing
intersections, parking, stopping, maneuvering
and other actions). This is a variant when the
road traffic is carried out on the existing roads
network, but the responsibility for the group
movement of vehicles is assigned to the driver-
instructors.
Nowadays, an example of the implementation of
the second model is a project Sartr led by Ricardo
UK Ltd. This project involves collaboration of the
participating companies: IDIADA and Robotiker-
Tecnalia of Spain, Institut for Kraftfahrwesen
Aachen (IKA) of Germany, SP Technical Research
Institute of Sweden, Volvo Car Corporation and
Volvo Technology Sweden (green.autoblog.com,
2012).
The project aims to create a new model of
personal transportation by organizing environmental
auto-trains.
The new system will facilitate the safe
movement of auto-trains on the UN-modified public
roads in the close interaction with other participants
of the road traffic.
The proposed scheme provides controlling
functions and responsibility for an auto-train
movement for a professional driver who is driving
the leading car. The rest of the vehicles of an auto-
train are moving in a semi-autonomous control
mode, allowing the drivers of these vehicles to keep
less driving control than usual, and to use their
mobiles, to read the books, to watch the videos, to
eat - to perform the actions that would normally be
disabled in an usual driving mode for personal safety
reasons (Sartre-project.eu, 2012).
However, the problem of the slave cars drivers’
involvement in the decision-making process in the
emergency cases is remaining unsolved. Usually, a
driver reaction time is 0.3-0.7 seconds. If you are
driving a car in a semi-automatic mode, the reaction
time will lay in a substantially larger range. A driver,
being in the middle of a road auto-train, would be
unable to act autonomously, so the classic method of
continuous inclusion of an operator in the
management of an object with operator’s dosed
workload does not solve the problem.
It must be also noted that the proposed option
should be considered as an intermediate and
compromise, because of the fact that it leaves
unresolved the issue of interaction on the road of a
human and a robot. Besides of that, the cost of an
unmanned vehicle is significantly higher than the
cost of a traditional one, primarily due to the more
complex devices that detect presence and behavior
of humans on the road. (There is no way to use
formal models and communication protocols of
machines on the road).
2.3 Underlying Communication
and Network Technologies
To ensure interoperability between different wireless
technologies the use of concordant protocols for
wireless data transmission networks is required. The
most important requirement is scalability of
frequency bands, the same for the different
technologies, and standardization of the frequency
spectrum. Besides that the flexible means of
adaptation and adjustment of the system, including
the antenna systems are demanded. The full set of
requirements for the standard international mobile
wireless broadband 4G network is specified in IMT-
Advanced standard. And the list of requirements for
adaptive antenna systems using Dynamic Digital
Beamforming is included in promising LTE-
Advanced and WiMAX standards. Thus, 4G systems
will be coordinated with IMT-Advanced set of
standards. At the user level, they will be
distinguished by high data transfer speed – over 100
Mbit/sec for mobile subscribers (Msadaa, 2010).
At the technological level 4G systems will be
characterized by:
complete transition to the OFDM modulation
(working in multipath conditions);
consistent coordinated work on the physical
protocol layer;
high flexibility in selecting of the frequency bands
and frequency ranges, adaptive tuning of
modulation methods;
application of the most accomplished methods of
the channel correcting coding.
The full transition to IPv6 protocol will allow
building IP networks over the roads networks. To
increase bi-directional flow of messages at the mesh
networks the following problems have to be solved:
providing functional interoperability of mesh
devices;
increasing efficiency of the network protocols;
improving the quality of the data transport
services;
reducing delays of the information transmission in
the data networks.
For a wide range deployment of the mesh
networks compatibility with existing network
standards and protocols is needed, when available
such compatibility would allow a large set of mesh
networks from different manufacturers to
interoperate at physical, channel and network levels
ICINCO2013-10thInternationalConferenceonInformaticsinControl,AutomationandRobotics
444
of OSI, including IPv4 and IPv6 protocols. The
network would be able to combine the devices
having different wireless interfaces. Currently, Intel
Corporation is working on solving this compatibility
problem at the level of a radio transmission system
changeover, adaptable to any wireless
communication environment. This approach is
significantly less expensive than implementing
multiple wireless interfaces in each device (Suh,
2009).
3 CONCLUSIONS
Analysis of ways to improve the safety of road
traffic management revealed the existence of the
objective contradictions while trying at the same
time to allow operation of unmanned vehicles and
conventional vehicles driven by drivers. The most
promising option to reduce accidents on the roads
and transportation costs will be the use of
independent lanes or even highways for unmanned
vehicles movement with traffic regulations allow the
movement in the column, and one by one.
The increase in bi-directional flow of messages,
providing computerized support of road traffic,
generates the new requirements for the informational
maintenance of the data networks. Due to the
constantly increasing amount of data transmitted it
makes sense to separate the task of building a mobile
mesh network as an independent component.
Solving this problem at another level independently
from other applications will reduce the load on the
mobile networks data link channels by the margin of
15-20%.
A key issue is the integration of mobile resources
to a regional infrastructure, involving continuous
connection of a vehicle with the traffic control
services, manufacturer’s service centers, and also
communicating directly with the neighboring
vehicles in a given radius without access to the
global data transmission networks. Integration of
mobile resources implies the development and
widespread usage of compatible networking
equipment.
REFERENCES
Mazda.com, 2013. Safety system. (online) Available at:
http://www.mazda.com/mazdaspirit/functionality/oper
ability/operability5.html (Accessed 15 March 2013).
Audi.com, 2013. Audi night vision. Innovative driver
assistance system. (online) Available at:
http://www.audi-electronics-venture.de/aev/brand/en/
projects/audi_night_vision.html (Accessed 15 March
2013).
Mobileye.com, 2013. Traffic Sign Detection. (online)
Available at: <http://www.mobileye.com/
technology /applications/traffic-sign-detection/
(Accessed 15 March 2013).
Media.ford.com, 2013. Ford Lane Keeping System Helps
Fusion Drivers Stay Alert and Between the Lines.
(online) Available at: http://media.ford.com/
article_display.cfm?article_id=35776 (Accessed 15
March 2013).
Media.ford.com, 2012. Adaptive Cruise Control and
Collision Warning with Brake Support. (online)
Available at: http://media.ford.com/images/
10031/Adaptive_Cruise.pdf (Accessed 15 March
2013).
Euroncap.com, 2010. Mercedes-Benz’s basic PRE-SAFE.
(online) Available at: http://www.euroncap.com/
rewards/mercedes_benz_pre_safe_brake.aspx
(Accessed 15 March 2013).
Mydigitallife.info, 2008. Toyota Develops Automatic
Brake System Assisted by GPS Technology for Safety
Driving. (online) Available at:
http://www.mydigitallife.info toyota-develops-
automatic-brake-system-assisted-by-gps-technology-
for-safety-driving/ (Accessed 15 March 2013).
Autoevolution.com, 2011. How Does Mercedes Pre-Safe
Work. (online) Available at: <http://
www.autoevolution.com/news/how-does-mercedes-
pre-safe-work-6535.html (Accessed 15 March 2013).
Ford.co.uk, 2012. News from Ford. Ford’s Sync
Emergency Assistance could provide important
support to road accident victims says AA president.
(online) Available at: http://www.ford.co.uk/
experience-ford/AboutFord/News/CompanyNews/20
12/Fords-Sync-Emergency-Assistance (Accessed 15
March 2013).
Census.gov, 2012. The 2012 Statistical Abstract
Transportation: Motor Vehicle Accidents and
Fatalities. (online) Available at:
http://www.census.gov/compendia/statab/cats/transpor
tation/motor_vehicle_accidents_and_fatalities. html
(Accessed 15 March 2013).
Robots.ox.ac.uk, 2012. RobotCar Uk. How it works
Fatalities. (online) Available at:
http://mrg.robots.ox.ac.uk/robotcar/howitworks.html
(Accessed 15 March 2013).
En.wikipedia.org, 2013. Google driverless car Fatalities.
(online) Available at: http://en.wikipedia.org/
wiki/Google_driverless_car (Accessed 15 March
2013).
Greencarcongress.com, 2011. Nevada enacts law
authorizing autonomous (driverless) vehicles. (online)
Available at: http://www.greencarcongress.com/
2011/06/ ab511-20110625.html (Accessed 15 March
2013).
Sartre-project.eu, 2012. The SARTRE Project. (online)
Available at: http://www.sartre-project.eu/en/
Sidor/ default.aspx (Accessed 15 March 2013).
RoadTrafficEfficiencyandSafetyImprovementsTrends
445
Green.autoblog.com, 2012. Volvo's Sartre road train's
autonomous cars go 50 mph over 120 miles in Spain.
(online) Available at: http://green.autoblog.com/
2012/05/29/volvos-sartre-road- rains-autonomous-
cars-go-50-mph-in-spain/ (Accessed 15 March 2013).
Ikbal Chammakhi Msadaa, Pasquale Cataldi, and Fethi
Filali. 2010. A Comparative Study between 802.11p
and Mobile WiMAX-based V2I Communication
Networks. In Proceedings of the 2010 Fourth
International Conference on Next Generation Mobile
Applications, Services and Technologies (NGMAST
'10). IEEE Computer Society, Washington, DC, USA,
186-191.
Suh, Seong-Youp, 2009, Multiprotocol antenna structure
and method for synthesizing a multiprotocol antenna
pattern, US Patent US2010042396.
ICINCO2013-10thInternationalConferenceonInformaticsinControl,AutomationandRobotics
446
