Article
citation information:
Czech, P., Turoń, K., Barcik,
J. Autonomous vehicles: basic issues. Scientific
Journal of Silesian University of Technology. Series Transport. 2018, 100, 15-22. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2018.100.2.
Piotr CZECH[1],
Katarzyna TUROŃ[2],
Jacek BARCIK[3]
AUTONOMOUS
VEHICLES: BASIC ISSUES
Summary. The work was dedicated
to the subject of innovative autonomous vehicles on the transport market. The
paper presents basic information about autonomous cars: a nomenclature
characteristic of autonomous vehicles, along with the terms
“automatic”, “autonomous”, “self-drive” and
“driverless”. The article also presents various types of
autonomous cars based on the most popular classifications in the world. The
purpose of the work is to present basic issues related to autonomous vehicles.
Keywords: autonomous vehicles; autonomous vehicles
nomenclature; classification of autonomous vehicles; autonomous vehicles in
transport systems.
1. INTRODUCTION
Significant technological
development and the increase in the importance of comfort during travelling and
driving have led to the search for various types of automotive solutions. which
would allow for travelling in a much more convenient way. This kind of trend
has brought with it the emergence on the market of systems that can improve
driving safety and thus automate it. Such solutions include adaptive cruise
control (ACC), system warnings before running off a lane (AFIL), adaptive
lights (AFL), brake assist (BAS), brake assist systems warning of a vehicle in
the blind spot (BLIS), systems for monitoring driver fatigue (Driver
Alert/Attention Assist) [1-4]. There are also systems supported by artificial
intelligence, for example, for image analysis [5-9]. Despite equipping vehicles
with various types of car support systems, no accidents or collisions caused by
driver errors were avoided. At that time, the key factors in collisions or
accidents were human factors related to human driving skills, mental and
physical conditions or age, among others [10-13].
Due to the human
unreliability during the driving process, an attempt has been made to create
cars that can be driven on their own, where the role of the driver would be
limited to remaining a passenger of the vehicle. These types of cars are
autonomous vehicles.
Due to the fact that
autonomous vehicles are the current trend in the field of motorization, many
terms and divisions systematizing autonomous vehicles have been defined. The
paper presents the basic issues on autonomous cars. The authors explain the
definitions, the historical outline of autonomous vehicles in the world and the
most popular classifications of autonomous vehicles.
2. AUTONOMOUS CARS:
BASIC INFORMATION
The autonomous car (also
known as a self-driving car or a driverless car) is a vehicle that is capable
of sensing its environment and navigating without human input [13]. Autonomous
vehicles are driven using technology such as GPS, odometry, radars, laser
lights and computer vision [14-15]. Thanks to the use of these types of
technology, vehicles can identify the appropriate route, existing obstacles in
the way, connect with the road infrastructure and read the content of markings
[14-16].
Despite the fact that,
currently, autonomous cars are becoming a global trend, the first attempts to
create such solutions appeared as early as 1920 [17]. These were, however,
initial automation projects. Many attempts were made in the 1950s and then in
1980 [18]. The 2000s saw the gradual appearance of test vehicles from leading
automotive brands [18]. Despite the construction of vehicles, testing them on
public roads is not easy. This is due to the safety and necessity to adjust
traffic laws for autonomous vehicles.
At the end of 2013, four
US states (Florida, California, Michigan and Nevada) adopted legislation
permitting autonomous cars to travel on public roads [19]. Under this
legislation, state regulations have made it possible for 11 companies to test
vehicles [19]. In 2015, seven major automotive brands have been tested,
including Bosch, Delphi Automotive Systems, Google Auto, Nissan North America,
Mercedes-Benz Research & Development North America, Tesla Motors and the
Volkswagen Group of America [19].
Vehicle manufacturers
emphasize that the expected period when cars can appear on roads for use by
drivers is 2020-2030 [20]. In turn, the implementation of autonomous vehicles
on the market will cause a transport revolution [21]. Indeed, it will be one of
three revolutions that will change the face of current transport: steering
automated vehicles, shared vehicles and electric vehicles [22].
Autonomous cars are
supposed to bring many benefits to society. The advantages include increasing
mobility, limiting congestion, improving road safety by reducing collisions and
accidents, and having a positive impact on the environment [23].
3. NOMENCLATURE AND MAIN
CLASSIFICATIONS OF AUTONOMOUS VEHICLES
With the emergence of
test autonomous vehicles on the market, various types of nomenclature have been
circulated. These cars have been referred to as autonomous as well as
automatic/automated. However, they are not the same terms and the difference
between them is directly related to the degree of involvement of human support
in relation to the car’s functioning [24]. The vehicle, which is referred
to as “automatic” or “automated”, is a self-acting
machine, which has no intelligent systems [24]. In turn, the autonomous vehicle
will be equipped with intelligent systems, based on which it will be able to
make decisions, e.g., about the destination and changing the route according to
its own suggestions [24]. An automatic car can only perform commands [24].
Another difference in
the nomenclature of autonomous vehicles concerns the terms
“self-driving” and “driverless”. They differ at the
technological level. Self-driving is considered to refer to cars that are not
as technologically advanced as the driverless type [24,25].
The most famous division
of autonomous vehicles in the world is the so-called American classification,
as presented by National Highway Traffic Safety Administration (NHTSA) [26].
This division includes four levels of autonomous driving and a zero level [26].
The individual levels and their description are presented in Table 1.
Table
1
Autonomous
driving levels according to the NHTSA classification
Level |
Description |
0 |
The driver‘s task is to support all
systems in the vehicle. |
1 |
The vehicle is equipped with automatic versions of some systems (e.g., ESP systems, ABS, automatic
braking), which can be activated spontaneously or with the help of the
driver. However, the driver‘s task is to oversee
system functioning. |
2 |
The vehicle is equipped with automatic systems
that release the driver from having to operate them. Such systems include the system maintaining the vehicle in the lane and an adaptive tempomat. |
3 |
The vehicle is able to drive autonomously
under specific conditions, with the
driver coordinating the correct operation of
the systems. |
4 |
Full automation of the vehicle. The driver travels as a passenger without having to
interfere with the operation of automatic systems. |
Source:
[26]
In turn, the EU
distinguishes two main definitions of autonomous vehicles [27]: an autonomous
vehicle and an automated vehicle. For an automated vehicle, the EU considers a
vehicle equipped with technology, which allows the driver to transfer part of
his/her driving duties to on-board systems [28]. In turn, an autonomous vehicle
is a fully automated vehicle equipped with technologies allowing the system to
perform all functions related to driving without any human intervention [28].
Another classification
is the division according to the International Society of Automotive Engineers
(ISAE) from 2014 [29]. This classification includes five levels of autonomous
driving and a zero level. A detailed classification is presented in Table 2.
Table 2
Autonomous
driving levels according to the ISAE classification
Level |
Description |
0 |
Full control of the vehicle belongs to the
driver, even if the car is able to inform him/her about the hazards. The driver is responsible for monitoring the environment
and must be ready to take control. |
1 |
The vehicle is equipped with support for
particular aspects of driving, e.g., steering or acceleration/braking. The
driver is responsible for monitoring the environment and must be ready to
take control. |
2 |
Partial automation of the vehicle - the use of
the system for both driving and speed control; the
driver is responsible for the supervision and implementation of the remaining
driving elements. The driver is
responsible for monitoring the environment and must be ready to take control. |
3 |
Conditional automation of the vehicle -
the possibility of taking over by the car control of all aspects of
driving, assuming that the driver must be ready at any time to take control
of the car. |
4 |
High level of automation of the vehicle -
the car is able to take control of all
aspects of driving, even if the human driver does not respond to the call to
take control. |
5 |
Full automation of the vehicle
- independent driving under all
conditions. |
Source:
[29]
The next classification
comes from the German automotive industry association Verband Der Autoindustrie
(VDA) [30]. The association defines five levels of autonomous driving and a
zero level. A detailed classification is presented in Tab. 3.
Table 3
Autonomous driving levels according to the VDA
classification
Level |
Description |
0 |
In
the vehicle, there are no automated functions. The driver should control the
vehicle during driving (i.e., maintaining speed, accelerating and braking)
and lateral control (i.e., steering). There are active-only systems connected
with car warnings and problems. |
1 |
The vehicle is
equipped with a system that is able to assume either longitudinal or lateral
control of the car, during which the driver has to control all tasks in the
vehicle. |
2 |
The
vehicle is particularly automated. The driver does not have to manage
longitudinal and lateral control of the system in certain cases. The driver
has to monitor the vehicle in traffic during a journey and be ready to resume
control of the vehicle when the driver needs to. |
3 |
The
system knows the limits of its functioning and, in a situation where it
encounters an obstacle, the vehicle requests the driver to resume the task of
driving. The driver does not have to control and monitor the longitudinal and
lateral drive but is asked to exercise special caution because, at any
moment, the system may ask him/her to take control of the vehicle. |
4 |
The vehicle is able to
self-drive but only under certain conditions, for example, a specified type
of road or speed range. Under these conditions, the driver can become a
passenger of the car. |
5 |
The car is fully
autonomous. It is able to self-drive on all types of roads and adapt to all
speed requirements. The driver acts a passenger role. |
Source:
[29,30]
Due to the occurrence of various
types of classification, it is not an easy task to determine the current level
of autonomy of individual vehicles without referring to the specific
classification. Regardless of the type of the classification, the
aforementioned divisions have many common points and strive to achieve a fully
autonomous vehicle with the elimination of the need for human control.
4. SUMMARY
In conclusion, despite
the fact that autonomous vehicles seem to be an abstract issue for current
public road users, worldwide tests of vehicles in motion predict the appearance
of cars for public use in the near future. Such changes in transport will
certainly mean another revolution, which is why it is important to educate the
public in the field of dealing with autonomous vehicles. This education should
include appropriate behaviour on roads on which the vehicles will be able to
move. However, before cars are fully implemented on current transport systems,
it is important to familiarize the public with the applied nomenclature and the
division of vehicles due to the degree of autonomous driving. This will allow
society, in a more accessible way, to become acquainted with a new way of
moving, which, although it may seem abstract at the moment, represents the
future of transport. It is hoped that this work will act as an introduction to
learning the basic issues about autonomous vehicles.
References
1.
Vahidi
Ardalan, Azim Eskandarian. 2003. “Research advances in intelligent
collision avoidance and adaptive cruise control”. IEEE Transactions on Intelligent Transportation Systems 4(3):
143-153. ISSN: 1558-0016. DOI: 10.1109/TITS.2003.821292.
2.
Kusano Kristofer,
Gabler Hampton. 2012. “Safety benefits of forward collision warning,
brake assist, and autonomous braking systems in rear-end collisions”. IEEE Transactions on Intelligent
Transportation Systems Archive 13(4): 1546-1555. ISSN: 1524-9050. DOI: 10.1109/TITS.2012.2191542.
3.
Kato
Shin, Sadayuki Tsugawa, Kiyohito Tokuda, Takeshi Matsui, Haruki Fujii. 2002.
“Vehicle control algorithms for cooperative driving with automated
vehicles and intervehicle communications”. IEEE Trans. Intelligent Transportation Systems 3(3). ISSN:
1558-0016. DOI: 10.1109/TITS.2002.802929.
4.
Schöneburg Rodolfo, Karl-Heinz Baumann., Justen Rainer. 2003.
“Pre-safe - the next step in the enhancement of vehicle safety”. In
18th International Technical Conference
on the Enhanced Safety of Vehicles, Transport Research Laboratory 1-8. ISBN: 0115511121.
5.
Ogiela
Lidia, Ryszard Tadeusiewicz, Marek Ogiela. 2006. “Cognitive analysis in
diagnostic DSS-type IT systems”. In Eighth
International Conference on Artificial Intelligence and Soft Computing.
Zakopane, Poland. 25-29 June 2006. Artificial
Intelligence and Soft Computing - ICAISC 2006: 962-971. Book series: Lecture Notes in Computer Science 4029.
6.
Ogiela
Lidia, Ryszard Tadeusiewicz, Marek Ogiela. 2006. “Cognitive computing in
intelligent medical pattern recognition systems”. In Huang D.S., Li K., Irwin
G.W (eds.) International Conference on
Intelligent Computing. Kunming, P.R. China. 16-19 August 2006. Intelligent Control and Automation:
851-856. Book series: Lecture Notes in
Control and Information Sciences 344.
7.
Ogiela Marek,
Ryszard Tadeusiewicz, Lidia Ogiela. 2005. “Intelligent semantic
information retrieval in medical pattern cognitive analysis”. In Gervasi O., Gavrilova M.L., Kumar V. et al. (eds.) International Conference on Computational Science and Its Applications.
Singapore. 9-12 May 2005. Computational
Science and Its Applications - ICCSA 2005 Vol. 4: 852-857. Book series: Lecture Notes in Computer Science 3483.
8.
Tadeusiewicz
Ryszard, Lidia Ogiela, Marek Ogiela. 2008. “The automatic understanding
approach to systems analysis and design”. International Journal of Information Management 28(1): 38-48.
9.
Dyakov
I., O. Prentkovskis. 2008. “Optimization problems in designing
automobiles”. Transport 23(4):
316-322.
10.
Dresner
Kurt, Peter Stone. 2006. “Traffic intersections of the future”. In Proceedings of the 21st National Conference
on Artificial Intelligence NECTAR
Track 2: 1593-1596. Palo Alto, CA: AAAI Press. Accessed: 30 June 2018.
Available at: https://www.aaai.org/Papers/AAAI/2006/AAAI06-258.pdf.
11.
Gehrig
Stefan, Fridtjof Stein.1999. “Dead reckoning and cartography using stereo
vision for an autonomous car”. In Proceedings 1999 IEEE/RSJ
International Conference on Intelligent Robots and Systems. Human and
Environment Friendly Robots with High Intelligence and Emotional Quotients
(Cat. No.99CH36289), Kyongju, 3:
1507-1512. ISBN: 0-7803-5184-3. DOI:
10.1109/IROS.1999.811692.
12.
Wolcott
Ryan, Ryan Eustice. 2014. Visual localization within LIDAR maps for automated
urban driving. In IEEE/RSJ International
Conference on Intelligent Robots and Systems, Chicago: 176-183. ISSN:
2153-0866. DOI: 10.1109/IROS.2014.6942558.
13.
Kröger
Fabian. 2016. “Automated driving in its social, historical and cultural
contexts”. In Maurer Markus, Gerdes Christian, Lenz Barbara, Winner
Hermann (eds.) Autonomous Driving.
Technical, Legal and Social Aspects. New York, NY: Springer. ISBN:
978-3-662-48845-4. DOI: 10.1007/978-3-662-48847-8.
14.
Moras
Julien, Cherfaoui Véronique, Bonnifait Phillipe. 2010. “A lidar
perception scheme for intelligent vehicle navigation”. In 11th International Conference on Control
Automation Robotics & Vision, 1809-1814. ISBN: 978-1-4244-7815-6. DOI:
10.1109/ICARCV.2010.5707962.
15.
Howard Andrew. 2008. “Real-time stereo visual
odometry for autonomous ground vehicles”. In IEEE/RSJ International Conference on Intelligent Robots and Systems,
3946-3952. ISSN: 2153-0866. DOI: 10.1109/IROS.2008.4651147.
16.
Yuchao
Sun, Doina Olaru, Brett Smith, Stephen Greaves, Andrew Collins. 2017.
“Road to autonomous vehicles in Australia: an exploratory literature
review”. Road & Transport Research:
A Journal of Australian and New Zealand Research and Practice 26(1). ISSN:
1037-5783.
17.
John
W. 2014. Driverless Car: Autonomous Future in Your Garage. Scotts Valley, CA: CreateSpace Independent
Publishing Platform. ISBN: 978-1503287907.
18.
Wadhawa
Vivek, Alex Salkever. 2017. The driver in
the driverless car. how our technology choices will create the future, USA:
Berrett-Koehler Publishers. ISBN-13: 978-1626569713.
19.
Glassbrook
Alex. 2017. The law of driverless cars:
an introduction, USA: Law Brief Publishing. ISBN-13: 978-1911035282.
20.
Sudha
Jamthe. 2017. 2030 The Driverless World: Business Transformation from Autonomous
Vehicles, Stanford:
CreateSpace Independent Publishing Platform. ISBN-13: 978-1973753674.
21.
Hermann Andreas, Walter Brenner, Rupert, Stadler.
2018. Autonomous Driving: How the
Driverless Revolution Will Change the World. Somerville, MA: Emerald
Publishing Limited. ISBN: 1787148343.
22.
Sperling Daniel. 2018. Three Revolutions: Steering Automated, Shared, and Electric Vehicles to
a Better Future. Washington, DC: Island Press. ISBN: 9781610919050.
23.
Zanchin Betina, Rodrigo Adamshuk Silva, Max Mauro
Santos, Max Mauro, Kathya Linares. 2017. “On the instrumentation and
classification of autonomous cars”. In IEEE International
Conference on Systems, Man, and Cybernetics, 2631-2636, DOI:
10.1109/SMC.2017.8123022.
24.
Levinson David. 2017. “On the differences
between autonomous, automated, self-driving, and driverless cars”.
Available at:
https://transportist.org/2017/06/29/on-the-differences-between-autonomous-automated-self-driving-and-driverless-cars/.
25.
Bargelis A., A. Baltrušaitis. 2013. “Applications of virtual
reality technologies in design and development of engineering products and
processes”. Mechanika 19(4):
673-676. DOI: http://dx.doi.org/10.5755/j01.mech.19.4.5057.
26.
National Highway Traffic Safety Administration
(NHTSA). “Automated vehicles for safety”. Available at:
https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety.
27.
European
Union. Briefing: Automated Vehicles in
the EU. Available at:
http://www.europarl.europa.eu/RegData/etudes/BRIE/2016/573902/EPRS_BRI(2016)573902_EN.pdf.
28.
International
Society of Automotive Engineers. Automated
Driving. Available at: https://www.sae.org/misc/pdfs/automated_driving.pdf.
29.
Verband
der automobilindustrie (VDA). “Automation from driver assistance systems
to automated driving”. Available at:
https://webcache.googleusercontent.com/search?q=cache:rB5YVdzyLdwJ:https://www.vda.de/en/topics/innovation-and-technology/automated-driving/automated-driving.html+&cd=2&hl=pl&ct=clnk&gl=pl.
30.
Samociuk
W., Z. Krzysiak, G. Bartnik, A. Skic, S. Kocira, B. Rachwal, H. Bakowski, S. Wierzbicki,
L. Krzywonos. 2017. “Analysis of explosion hazard on propane-butane
liquid gas distribution stations during self tankage of vehicles”. Przemysl Chemiczny 96(4): 874-879. DOI:
10.15199/62.2017.4.29.
Received 20.04.2018; accepted in revised form 18.08.2018
Scientific
Journal of Silesian University of Technology. Series Transport is licensed
under a Creative Commons Attribution 4.0 International License
[1] Faculty of Transport, Silesian
University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland.
Email: piotr.czech@polsl.pl.
[2] Faculty of Transport, Silesian
University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland.
Email: katarzyna.turon@polsl.pl.
[3] The Faculty of Law and
Administration at the University of Silesia, Bankowa 11b Street, 40-007
Katowice, Poland. Email: jacek.barcik@us.edu.pl.