autonomous cars - recent development

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ŠKODA AUTO UNIVERSITY Seminar Work Topic: Autonomous cars recent development and the future New Trends in Automotive Industry January 2015 Lucie Tajovská

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1) Definition and Classification2) Potential + Advantages of Autonomous Cars3) Challenges and Barriers to introducing Autonomous Cars4) Previous visions regarding Autonomous Cars5) Current developments: Technological status quo6) Future prognosis

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Page 1: Autonomous Cars - Recent Development

ŠKODA AUTO UNIVERSITY

Seminar Work

Topic: Autonomous cars – recent

development and the future

New Trends in Automotive Industry

January 2015

Lucie Tajovská

Page 2: Autonomous Cars - Recent Development

1

1 Definition and Classification

An autonomous car, also called a driverless car, a robot car or self-driving car is in

general a „computer controllled car that drives itself“ [1]. Acording to one of the

definitions, the term autonomous is described as „having the power for self-

government“ [2]. In the context of autonomous cars it implies that the vehicle can

complete a transport operation without any interference from humans, except

initiating the operation. There are several levels of the vehicle’s autonomity. An

NTHTSA, the National Highway Traffic Safety Adminitraton, has created an official

classification system, scoring vehicles on thier automation level [3]:

No-Automation (Level 0): The driver completely controls the vehicle.

Function-specific Automation (Level 1): certain vehicle functions are

automated, such as system of electronic stability control or automatic

braking.

Combined function Automation (Level 2): At least two controls can be

automated and work together in key situations

Limited Self-Driving Automation (Level 3): An example of this category is

the well-known Google car. The car is capable of performing of all driving

functions, assuming the driver is available for occasional control.

Full Self-Driving Automation (Level 4): The vehicle is fully automated and

performs all safety-critical functions, while the driver, or rather the

passenger, is not expected to control the vehicle. As this vehicle would

control all functions from start to stop, including all parking functions, it

could include unoccupied cars [4].

2 Potential + Advantages of Autonomous Cars

Reducing accident rate is the main advantage of autonomus cars, as more than

90% of all accidents are caused by the operators' (drivers) incapacitation,

distraction or misjudgment [5]. Replacing the human operator with an automated

system not prone to the same deficiencies can therefore potentially reduce the

number of road accidents to almost none; in turn saving society large resources

currently absorbed by health care, insurance and premature deaths.

Page 3: Autonomous Cars - Recent Development

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Allowing groups of people unable to operate a car the same mobility as drivers.

These groups could be very old people, children/youngsters, disabled and people

who are on medication preventing them from driving.

There is also a potential for a self-parking car, as parallel parking represents a

major undertaking for many people. As of January 2015, BMW is about to present

a car, that can drop-off passengers and then park on its own [6]. Mercedes in its

Luxury in Motion Concept has taken it even further – the car can actually find

parking on its own and return when summoned. Pedestrians are of course taken

into consideration [7]. The major challenge lies of course in cars equiped with

intelligence adequate to deal with all the complexity of real-life environment and

unusual situations.

Driverless vehicles transporting cargo between manufacturers and from

manufacturers to retailers or direct delivery to consumers. This has the potential of

significantly reducing the cost of cargo transport as a human operator is not

needed for most of the operation; only loading and offloading of the vehicle would

require human intervention - and even these operations could prospectively be

automated.

3 Challenges and Barriers to introducing Autonomous Cars

The main challenge to operating autonomous cars and cargo vehicles is the

tremendous complexity of the environment wherein the vehicles will operate. The

environment include other vehicles of course, bikers, pedestrians, animals and

virtually any imaginable object blocking the transport corridor. And all of these can

potentially move in any direction at any speed. Add to this that weather conditions

can restrict visibility and change the way the vehicle reacts to physics... e.g. how

quickly a vehicle can change direction on a wet surface while still being under full

control of the operator.

All these complexities place huge demands on the flexibility of sensors and the

processing capability of the intelligence ensuring the safe operation of the

vehicles. The human eye and brain in combination have far more processing

capacity (in most circumstances) than any automation system based on artificial

intelligence developed to date. But unfortunately the human processing of data

Page 4: Autonomous Cars - Recent Development

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doesn't always lead to the same result; which result in the before mentioned driver

attributed accidents.

Artificial intelligence offers more consistent and uniform data processing, but

processing capacity is lower and slower; just as the capability of sensors like

cameras, radar, laser-rangers and similar can distort data processing if they are

not in perfect working order or conditions reduce their performance.

There's also a legal challenge to introduce autonomous vehicles; namely the

question of responsibility for accidents, damages or even death of humans.... all of

which relate to the issue of insurance. With a human operator the responsibility

question is easy to answer.... the current human operator has the responsibility.

When a computer or artificial intelligence is the operator then it becomes close to

impossible to identify who are responsible. Is it the system designer, the

manufacturer, the retailer, the system maintainer, the user or the owner? The

insurance companies and car manufacturing industries in a dialogue with

governments are still trying to find a solution to this problem...

4 Previous visions regarding Autonomous Cars

Previous decades ideas generally concentrated on reducing the complexity of the

environment wherein the autonomous vehicles would operate. This strategy was

caused by the available technology only a few decades ago, which did not allow

for the complex and fast processing of data that most people take for granted

today.

Dedicated lanes or entirely segregated roads - often called guideways - would

allow the safe operation of autonomous cars with relatively simple sensors and

modest processing capacity. These ideas very often included supply of energy

(electricity) to the autonomous vehicles via a power rail along the before

mentioned guideways. One sub-set of these ideas are dual-mode vehicles;

meaning vehicles under autonomous control when driving on segregated

guideways while human operated when driving on conventional roads.All these

systems generally only exists as concepts; in a few cases with basic prototypes

built. They have names like RUF, BiModal Glideway and HiLoMag [8].

Page 5: Autonomous Cars - Recent Development

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5 Current developments: Technological status quo

The present state of research and development is somewhere between Level 2

and Level 3 on the classification system described earlier. Many production cars

are already equipped with 2 or more automation system easing the driving task for

the operator, e.g. automatic lane-keeping and automatic braking if an object (other

car) is detected within a safety zone in front of the car. Level 2 automation is

rapidly approaching product maturity as more and more series-produced cars are

equipped with these systems, which also benefits from the practical experience

gained from having many systems in operation.

Level 3 automation, i.e. cars that are fully automated under certain situations,

exists in advanced prototypes and is in increasing numbers being demonstrated to

journalists and other members of the public. These systems cannot cope with the

full complexity of the environment of for example an inner city, but are intended to

be used primarily in environments where the complexity is significantly reduced;

the most obvious possibility being normal highways where the only type of object

expected are other moving cars and vehicles, all moving in the same direction and

at roughly the same speed. Level 3 automation relies on vehicle mounted sensors

working in conjunction with onboard computers and electronic maps of high

precision. All these things are almost ready for production, but one element of the

system is not completely ready and will take some time to field. This element is

vehicle-to-vehicle communication (V2V), which is necessary to warn vehicles - and

their drivers - about conditions that would require the driver to switch off the

automation and revert to manual control.

Level 3 automation does not have legal implications as the driver is responsible for

deciding when and where to drive in automatic mode automation and therefore it is

still the driver who are fully responsible if the use of automation causes an

accident. Since there is no legal barriers and the technology is at an advanced

prototype stage we can expect to see the gradual introduction of Level 3

automation within a few years...

Page 6: Autonomous Cars - Recent Development

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6 Future prognosis

The final stage of automation, Level 4 in the above mentioned classification

system, and what most people would probably consider a truly self-driving car is

still not ready to be introduced to the public. The main problem is still the

complexity of the driving environment and the way the artificial intelligence

interprets the input from sensors. It is still some way from being able to interpret

very varied and unpredictable inputs in the same way as humans do. Humans also

take social context into consideration, for example a uniformed person moving his

or her arms in a certain way can be a signal to the driver to stop the vehicle.

Artificial intelligence would not understand such a context and there is significant

disagreement when - if at all - it will be capable of such advanced data processing.

When 500 experts in automation technology were surveyed about the prospects of

completely autonomous cars more than half said they would be a reality in 2030 at

the very earliest; 20% expected it to be 2040 while a minority of 10% did not

expect it to be possible ever... [9]

Page 7: Autonomous Cars - Recent Development

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Resources

[1] http://www.pcmag.com/encyclopedia/term/57132/autonomous-vehicle

[2]

https://books.google.hu/books?id=59z6AwAAQBAJ&printsec=frontcover&dq=inaut

hor:%22Stetz,+Thomas%22&hl=sk&sa=X&ei=nHy6VPaiHYXNygOy2YL4CA&ved

=0CCAQ6AEwAA#v=onepage&q&f=false

[3] http://www.thecarconnection.com/news/1084651_nhtsa-lays-out-groundrules-

for-autonomous-vehicles

[4] http://en.wikipedia.org/wiki/Autonomous_car

[5] http://www.alertdriving.com/home/fleet-alert-magazine/international/human-

error-accounts-90-road-accidents

[6] http://www.techtimes.com/articles/22848/20141224/bmw-previews-wearable-

tech-self-parking-valet-mashup.htm

[7] http://www.autotrader.com/research/article/car-news/233807/mercedes-benz-f-

015-luxury-in-motion-concept-detroit-auto-show.jsp

[8] http://faculty.washington.edu/jbs/itrans/dualmode.htm

[9] http://www.technologyreview.com/news/529466/urban-jungle-a-tough-

challenge-for-googles-autonomous-cars/