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Legal aspects of autonomous vehicles – an overview (pre-print)

Authors:
  • Water Construction Company, State Enterprise (Vodohospodárska Výstavba, Štátny Podnik)

Abstract

The main goal of this article is to provide up-to-date information about legal regulation of autonomous vehicles (AVs) in Europe and the United States of America (U.S.). The legal overview is primarily intended for technical professionals for the purpose of giving them a holistic approach to AVs. The authors believe that technical professionals have to be aware of legal regulation of AVs as well in order to get the opportunity to discuss the feasibility of different legal statements. Besides the definition of AVs based on levels of automation, the article also contains answers to following questions: What are the greatest benefits of AVs? How does the general road traffic law need to be changed to allow the use of AVs on public roads? What are the differences between the current state of AV regulations in the U.S. and Europe? Finally, the paper draws attention to the most significant legal challenges that AVs address to lawmakers, insurance companies, consumers, and last but not least, car manufacturers.
Legal aspects of autonomous vehicles an overview*
Viktória Ilková
Faculty of Law
Comenius University in Bratislava
Slovak Republic
viktoria.ilkova1991@gmail.com
Adrian Ilka
Department of Signals and Systems
Chalmers University of Technology
Gothenburg, Sweden
adrian.ilka@chalmers.se
AbstractThe main goal of this article is to provide up-to-
date information about legal regulation of autonomous vehicles
(AVs) in Europe and the United States of America (U.S.). The
legal overview is primarily intended for technical professionals
for the purpose of giving them a holistic approach to AVs. The
authors believe that technical professionals have to be aware of
legal regulation of AVs as well in order to get the opportunity to
discuss the feasibility of different legal statements.
Besides the definition of AVs based on levels of automation,
the article also contains answers to following questions: What are
the greatest benefits of AVs? How does the general road traffic
law need to be changed to allow the use of AVs on public roads?
What are the differences between the current state of AV
regulations in the U.S. and Europe? Finally, the paper draws
attention to the most significant legal challenges that AVs address
to lawmakers, insurance companies, consumers, and last but not
least, car manufacturers.
Keywordsautonomous vehicle; traffic law; legal challenges;
liability
I. INTRODUCTION
Artificial intelligence, robots, 3D tissue printing,
autonomous vehicles. A few years ago we met these modern
technical innovations only in science fiction movies. However,
nowadays these inventions have become reality and in the near
future they will surround us more and more, until they will be
part of our lives [1], [2], [3], [4]. Though, the everyday use of
autonomous vehicles might seem futuristic, prognoses predict
their wide use in the near future [5].
According to the most general definition, an autonomous
vehicle (AV) is such a vehicle that can guide itself without
human conduction [6]. Use of the term “autonomous in
connection with motor vehicles has sometimes been
misunderstood because in some areas of law the concept of
autonomy is associated with broad philosophical concepts.
In contrast, the word “autonomous” in a technical context
simply means (more or less) that it works independently of
human input while driving. An “autonomous system” is
therefore a technical unit which fulfills certain tasks without
being dependent regular human commands [7]. A more
specific definition of AVs is provided by SAE International1
* This work was supported by the Chalmers Area of Advance Transportation,
by Vinnova under the FFI project MultiMEC and by Vinnova under FFI
project VCloud II, which is gratefully acknowledged.
1 SAE International (Society of Automotive Engineers) is a global association
committed to being the ultimate knowledge source for the engineering
profession.
through stating levels of automation. The extent of automation
depends on the human driver’s role in performing the dynamic
driving task (see Chapter II.) [8].
According to statistical information provided by the Police
Force of the Slovak Republic, there are on average 14 000
road traffic accidents in Slovakia per year causing over 7 000
personal injuries, from which ca 300 are fatalities2 [9].
Developers of autonomous technology estimate that autono-
mous vehicles could reduce traffic fatalities by 90%, which
would mean 270 saved lives per year in Slovakia [10]. The
benefits do not stop with safety. Autonomous vehicles have
the potential to transform personal mobility and open doors to
people with disabilities, aging populations, and communities
where car ownership is prohibitively expensive, or those who
prefer not to drive or own a car. Cities will reconsider how
space is utilized and how public transit is provided.
Infrastructure capacity could be increased without pouring a
single new truck load of concrete. Autonomous vehicles may
also have the potential to save energy and reduce air pollution
from transportation through efficiency and by supporting
vehicle electrification [11].
In Europe, cities in Belgium, France, Italy and the UK are
planning to operate transport systems for driverless cars, and
Germany, the Netherlands, and Spain have allowed testing
self-driving cars in traffic [12], [13]. The Swedish car
manufacturer company, Volvo has started to test 100 of its
autonomous cars on public roads driven in normal traffic by
regular clients by 2017. The company announced a
collaboration with Swedish legislators and transport
authorities to test the cars on a 30-mile road section around
Gothenburg by 2017, marking Volvo’s first public pilot of
fully autonomous vehicles. Analysts predict that completely
autonomous cars will be for sale by 2025-2030 [14], [15].
As autonomous technology gradually erodes driver
control, the law must be altered in its code and its
implementation. It is a significant challenge; but not an
insurmountable one. Therefore, any research question related
to the legal regulation of autonomous vehicles is increasingly
necessary and required, especially in Europe. One of the most
important and considerable issues is liability of autonomous
vehicles. The research within this topic is currently ongoing in
U.S. and Europe as well. This has been reported recently in
several publications [16], [17].
2 The average values are calculated based on data from 2011 to 2016.
Statistical information is available online, at the Slovak Ministry of Interior's
webpage.
In a European context, a new project called AdaptIVe
(Automated Driving Applications and Technologies for
Intelligent Vehicles) [18], has been established. The project
has many participants, mainly research institutions, including
some legal research groups. One of the most significant
participants is legal scholar Professor Eric Hilgendorf. At his
research center, called “RobotRecht”, he manages the Europe-
wide research on legal implications of autonomous vehicle
systems. As it is evident from the center's publications, the
research also covers the issue of liability [19].
The significance of this research area is proved by
numerous studies (as it can be seen in the references). Inter
alia, in early 2014, IHS Automotive released “Emerging
Technologies: Autonomous Cars Not If, But When”, a study
projecting a global total of nearly 54 million autonomous cars
by 2035, and predicting that almost all of the vehicles in use
are likely to be autonomous cars or autonomous commercial
vehicles sometime after 2050 [20]. The result will be a driving
environment that is far safer than what we are accustomed to
today.
II. LEVELS OF AUTOMATION
Before dealing with any further research questions related
to AVs, it is particularly necessary to acquire a sort of
taxonomy stating clear and categorical distinctions between
different modes (levels) of automation.
The mentioned taxonomy can significantly help to easily
differentiate AVs depending on who is responsible for
monitoring the driving environment.
Furthermore, stating clear levels of automation eliminates
confusion and is useful across numerous disciplines
(engineering, legal, media, and public discourse).
As mentioned in the Introduction, a global association of
automotive engineers called SAE International carried out a
report concerning levels of automation for defining driving
automation in on-road motor vehicles (also known as standard
J3016™) [8]. It has been adopted in September 2016 by the
U.S. Department of Transportation in Federal Policy for safe
testing and deployment of AVs [21]. Furthermore, the
organization signed an agreement with the German Institute of
Standardization, which fortifies the acceptance of SAE
automation levels as the global standard [22]. Thus, it has
become “the core reference and a guideline for all
stakeholders in this transformational technology”.3
The report defines six levels of driving automation span
from no automation to full automation. Elements indicate
minimum system capabilities for each level. A key distinction
is between level 2, where the human driver performs part of
the dynamic driving task, and level 3, where the automated
driving system performs the entire dynamic driving task. The
term "dynamic driving task" includes the operational (steering,
braking, accelerating, monitoring the vehicle and roadway)
and tactical (responding to events, determining when to
change lanes, turn, use signals, etc.) aspects of the driving
task, but not the strategic (determining destinations and
waypoints) aspect of the driving task [8].
3 Quoted from David L. Schutt, PhD, Chief Executive Officer of SAE
International.
TABLE 1 SUMMARY TABLE ON LEVELS OF AUTOMATION (Copyright © 2014 SAE International).
SAE
level
Name
Narrative Definition
Execution of
Steering and
Acceleration/
Deceleration
Monitoring
of Driving
Environment
Fallback
Performance
of Dynamic
Driving
Task
Human driver monitors the driving environment
0
No
Automation
the full-time performance by the human driver of all aspects of the
dynamic driving task, even when enhanced by warning or
intervention systems
Human driver
Human driver
Human
driver
1
Driver
Assistance
the driving mode-specific execution by a driver assistance system of
either steering or acceleration/deceleration using information about
the driving environment and with the expectation that the human
driver perform all remaining aspects of the dynamic driving task
Human driver
and system
Human driver
Human
driver
2
Partial
Automation
the driving mode-specific execution by one or more driver assistance
systems of both steering and acceleration/deceleration using
information about the driving environment and with the expectation
that the human driver perform all remaining aspects of the dynamic
driving task
System
Human driver
Human
driver
Automated driving system (“system”) monitors the driving environment
3
Conditional
Automation
the driving mode-specific performance by an automated driving
system of all aspects of the dynamic driving task with the expectation
that the human driver will respond appropriately to a request to
intervene
System
System
Human
driver
4
High
Automation
the driving mode-specific performance by an automated driving
system of all aspects of the dynamic driving task, even if a human
driver does not respond appropriately to a request to intervene
System
System
System
Some
driving
modes
5
Full
Automation
the full-time performance by an automated driving system of all
aspects of the dynamic driving task under all roadway and
environmental conditions that can be managed by a human driver
System
System
System
All driving
modes
III. ROAD TRAFFIC LAW IN THE UNITED STATES AND EUROPE
A. United States of America
Foremost, the United States (hereinafter U.S.) dealt with
the issue of legalizing autonomous cars. In June 2011, the
Nevada Legislature passed a law to authorize the use of
autonomous cars. Nevada thus became the first jurisdiction in
the world where autonomous vehicles might be legally
operated on public roads [23], [24]. Nowadays, most of the
U.S. states deal with the basic legal status of autonomous
vehicles [25].
In terms of the form of government, the U.S. is federation;
therefore it is important to distinguish between actions carried
out by the federal government, and those that have been taken
by individual states.
As for the federal road traffic regulation, the National
Highway and Transportation Safety Administration (NHTSA)
issued an updated guidance for the safe development of AVs
in September 2016 [21]. The policy update has four parts:
vehicle performance guidelines, model state policy, NHTSA’s
current regulatory tools and possible new regulatory actions
NHTSA believes could be helpful in ensuring the safe
deployment of AVs. For potential AV manufacturers, the
policy includes a set of 15 best practices regarding the safe
pre-deployment design as well as development and testing of
AVs prior to commercial sale or operation on public roads.
(For more details, the reader is referred to the Appendix).
Regarding state actions since 2012, nine states (California,
Florida, Louisiana, Utah, Michigan, North Dakota, Tennessee,
Nevada, and Virginia) and Washington D.C. have passed
legislation pertaining to AVs. In December 2016, an online
legislative database was created, which provides up-to-date,
real-time information about state AV legislation [27].
September 2016 was a turning point in terms of the state
legislature as well: California transportation authorities made
two major changes in their policy on autonomous vehicles.
The first change, a new bill signed into law, gives the Contra
Costa Transportation Authority permission to test a pilot
project on public roads without having a driver behind the
wheel. Prior to this, the state only allowed public road testing
if a human driver was in the driver’s seat and “capable of
taking immediate manual control of the vehicle in the event of
an autonomous technology failure or other emergency.”
The bill requires the autonomous vehicles to be insured for
$5 million, for the self-driving automobiles to not exceed 35
miles per hour on the road, and for testing data to be shared
with the government and while placing geographic
restrictions. Testing can only take place at two locations: at a
former Concord Naval Weapons Station and current AV
testing facility, and at the San Ramon Bishop Ranch office
park.
The second change, revised draft regulations released by
California’s department of motor vehicles, can potentially
change how all self-driving vehicles are tested in the state by
rolling out the privileges given to the aforementioned pilot
program. If the law were pass (it is still under legislative
procedure) it will allow car manufacturers to test vehicles
deemed safe by the federal government on public roads
without licensed drivers. Instead of having a driver in the
vehicle, the newly proposed regulations require that a test
driver has two-way communication with a vehicle [28].
B. Europe
Concerning Europe, an examination of legislation in
European Union (hereinafter EU) member countries involving
major automotive industry partners France, Germany, Spain,
Sweden, and the United Kingdom reveals that none of these
countries currently has pertaining legislation connected to
autonomous vehicles. Tests, however, are being carried out
continuously and are expected to take place in several EU
countries under ad-hoc legal permits [26].
Almost all EU member countries (with the exception of
Spain and the United Kingdom) have signed and ratified the
Convention on Road Traffic, also known as the Vienna
Convention [29]. It is a multilateral international treaty of the
United Nations dealing with general traffic law. Until 23
March 2016, any legislation adopted by a signatory of the
Convention had to require a human driver to be in control of
the moving vehicle at all times (see Article 8 par. 1, 5 and
Article 13 par. 1).4 In 2016, a new paragraph called ‘5bis’ was
added to Article 8.5 As a result, automated vehicles will be
compliant with the Vienna Convention following the
amendment, provided that the system can be overridden by the
driver, or fulfils (future) requirements of the ECE regulations.6
Sweden and Belgium made some further amendment
proposals that are still waiting to be decided upon7 [30].
While Europe has certainly not been left behind in the race
of technical development of advanced autonomous vehicles,
the pressure is now rising for lawmakers, insurance companies
and manufacturers tasked with addressing legal and regulatory
questions which, until recently, have been left unanswered.
4 Article 8 paragraphs 1 and 5 of the Vienna Convention require that “[e]very
moving vehicle or combination of vehicles shall have a [person] driver,” and
“[e]very driver shall at all times be able to control his vehicle.” Article 13
paragraph 1 further requires that “[e]very driver of a vehicle shall in all
circumstances have his vehicle under control so as to be able to exercise due
and proper care and to be at all times in a position to perform all maneuvers
required of him.”
5 It is worded as follows: "Vehicle systems which influence the way vehicles
are driven shall be deemed to be in conformity with paragraph 5 of this Article
and with paragraph 1 of Article 13, when they are in conformity with the
conditions of construction, fitting and utilization according to international
legal instruments concerning wheeled vehicles, equipment and parts which
can be fitted and/or be used on wheeled vehicles (a footnote here refers to the
ECE Agreement of 1958 and the GTR Agreement of 1998).
Vehicle systems which influence the way vehicles are driven and are not in
conformity with the aforementioned conditions of construction, fitting and
utilization, shall be deemed to be in conformity with paragraph 5 of this
Article and with paragraph 1 of Article 13, when such systems can be
overridden or switched off by the driver.”
6 ECE (Economics Commission for Europe) 1958 Agreement, and 1998
Agreement on Global Technical Regulations.
7 The proposals call for a redesign of Article 8 paragraph 5bis as well as the
addition of two further paragraphs - “5ter” and “5quater” – to Article 8. They
intend to distinguish between automated driving functions that take over part
of the task of driving, the complete task of driving for a certain section of the
journey or the complete task of driving for the whole journey, from beginning
to end.
IV. LEGAL CHALLENGES IN THE EUROPIAN KONTEXT
A. Administrative Law
Legal issues related to AVs belong to the scope of mainly
three branches of law. One of them is administrative law,
which includes especially road traffic law in general (it covers
among others issues such as certification and licensing,
technical controls, road traffic rules, etc). It deals with stating
technical norms as well. The most important legal challenges
related to autonomous driving in the area of administrative law
are following:
Does autonomous driving have to require special driving
license? If so, shall it be national or international? Shall an
AV driver (“user”) be required to have a driving license at
all? Do there have to be any age requirements for AV
users? (Or a requirement to be sober?)
Should autonomous driving be allowed everywhere (on all
roads and every regions)? Should it be mandatory on
special roads or dedicated lanes?
Does autonomous driving have to follow all traffic rules?
If an AV violates a traffic rule, does it have to selfreport
to authorities?
Should there be an external indicator on the vehicle when
autonomous driving is engaged?
The research focusing on these questions is currently ongoing
as the main object of the first author’s rigorous thesis.
B. Civil Law
Civil law covers a wide range of legal challenges related to
AVs. The most significant challenge is connected with the
issue of civil liability. It includes on the on hand liability for
damage and/or injury, which is further connected with
insurance issues, and on the other hand, there is product
liability (a specific type of liability for damage and/or injury,
caused by a defective product).
In this regard, an article from a German insurance journal
is worth mentioning [5]. In the article, the author outlines two
possible conceptual approaches that would contribute to reach
clear liability rules pertaining to AVs and clear insurance
coverage. Furthermore, it would result in minimization of
litigation. The first approach is based on a compulsory motor
third party liability (MPTL) insurance under the regime of
strict liability by mandating AV manufacturers to contribute a
portion of the insurance for each individual vehicle. However,
manufacturers would be exempted from product liability for
injury and damage that is covered under the compulsory
MPTL insurance regime and that was caused by a product
defect affecting AV functionality, unless the defect is the
result of gross negligence. This approach is rather theoretical
than pragmatic due to possible administration difficulties.
According the second approach, which suggests product
liability to be further sharpened, the requirement of a product
defect should be omitted. Instead, the manufacturer should be
held liable for injury and damage caused by the way goods
acted (i.e. the way of their actions and behavior; their effect;
and the failure of the goods to act or to behave in a particular
way, or to have a particular effect). The main argument for
this approach is the following: while AVs will be much safer
than conventional cars, the technology in the product is so
complex that there is an uncontrollable residual risk of
malfunctioning even when the product is free from defects.
Hence, the legislation should introduce an irrefutable
presumption of a defect in a highly or fully automated vehicle
that causes an accident, unless the manufacturer can prove that
the autonomous vehicle functionality was not the cause of the
accident. The MTPL regime would in this alternative remain
identical to the first approach, except that manufacturers
would not be incorporated into the MTPL system.
C. Criminal Law
Autonomous driving-inspired legal challenges in the area
of criminal law include especially the issue of criminal
responsibility as well as protection against cybercrime and
hackers. In general, research in this area is dealing with the
following questions:
What crimes may be committed in context of autonomous
vehicles?
Who should be held responsible in case when using an AV
a crime is committed (the owner of the vehicle; the person
who is sitting in the driver’s seat if there is any kind of it;
the vehicle manufacturer; the mechanic who mounted the
autonomous technology to the vehicle or another entity)?
The incidents may happen under various circumstances.
Will the responsible subject change depending on these
circumstances and if so, how? What are basic model
scenarios of incidents related to the use of autonomous
vehicles?
How should the law react, if the criminally responsible
subject is a legal entity?
As for the criminal responsibility for harm caused by an
AV, according to most European states’ criminal codes, the
driver (or vehicle owner) may be charged with negligence
even if the AV was in control (in autonomous mode). If no
negligence is proved, the criminally responsible entity is the
manufacturer. Since in most cases, a vehicle manufacturer is a
legal entity, it is highly important to consider the issue of
corporate criminal responsibility. The European Union
countries do not have an identical legislation in this area.
Some countries' criminal codes (including the Slovak republic
as well) are built on the idea of personal guilt. These codes
would definitely need an amendment. Hence, any research
questions focusing on corporate criminal responsibility are on
high importance.
According to the relevant statements of the Slovak
Criminal Code,8 a vehicle driver (resp. owner) may be held
criminally responsible for causing death, harm (or creating
danger for another) by negligence, even if the autonomous
vehicle was in control [31]. It means that the driver acted
negligently, i.e. failed to exercise reasonable care. But what
constitutes reasonable care for the driver? Checking the
functioning of the elements of the car’s autonomous systems
at regular intervals? If so, the driver may be blamed because
s/he failed to examine properly whether the sensors or the
autonomous technology were functioning correctly before the
car was starting a journey. May the law require the driver to
8 Chapters 149, 157, 285 of Act of the Slovak republic No. 300/2005 Coll.
Criminal Code, as amended.
look under the algorithm hood? This statement results in the
following dilemma: autonomous systems are installed into the
car to relieve the driver of various driving tasks; however, the
driver remains responsible for monitoring that the autonomous
system is performing the driving tasks correctly, and, where
necessary, taking corrective actions. Therefore, the driver is
not allowed to pursue other activities like reading an email or
watching a film, let alone work or sleep at the same time he is
'in control' of the car. The potential utility of the autonomous
system for the driver (but not for road safety in general) is
therefore significantly reduced [7].
As mentioned above, by the use of autonomous vehicles,
the most potential crimes that may arise are mainly crimes
against life and health (especially unintentional offences, such
as causing another's death, causing bodily injury or illness or
creating danger to another). /In context of intention, it is also
an interesting question, whether a fully AV can commit an
intentional crime/. However, it must not be forgotten about a
relatively new phenomenon, the cybercrime. Since AVs are
governed by a kind of software facility, which can be an
object of several hacker attacks, it is specifically important to
ensure an adequate protection to vehicle users. This protection
has two aspects: on the one hand, the criminal aspect
protection against cybercrime provided by criminal codes, and
on the other hand, it is the development of appropriate security
system regulated by technical norms and standards.
V. CONCLUSION
Legal regulation of autonomous vehicles is a fairly
complex object of research, all the more exciting, though. The
most significant benefit of autonomous vehicles is a much
safer driving environment. Accidents, however, will always be
an aspect of motor vehicle travel and it must be decided who
is to be held responsible in such cases.
European Union countries have a legal framework that will
be well equipped to address and adapt to all the mentioned
challenges in legal regulation of autonomous vehicles that
arise in the coming years. Some (not radical) legislative
adjustments will probably be needed. However, having
considered the massive reduction of injuries and fatalities
caused by road accidents, and the other benefits of the
autonomous technology, it is absolutely worth making those
legal changes that will lead to clearer rules and practical
reality.
This in turn requires a broad cooperation of lawmakers and
technical professionals in order to achieve the most
appropriate solutions. That is exactly what we attend to call
for by the main contribution of the article which is giving a
brief insight to some legal aspects of autonomous vehicles for
technical professionals.
APPENDIX
Federal Automated Vehicles Policy issued by the U.S. National
Highway Traffic Safety Administration (NHTSA)
1. Vehicle Performance Guidance for Automated Vehicles
It is a 15 point “Safety Assessment” for the safe design, testing
and deployment of automated vehicles. The manu-facturer shall
send in a statement addressing the 15 points below. There is no
formal approval process.
Operational Design Domain: How and where the highly
automated vehicle (HAV) is supposed to function and
operate;
Object and Event Detection and Response: Perception-
and response functionality of the HAV system;
Fall Back (Minimal Risk Condition): Response and
robustness of the HAV upon system failure;
Validation Methods: Testing, validation, and verification
of an HAV system;
Registration and Certification: Registration and
certification to NHTSA of an HAV system;
Data Recording and Sharing: The HAV system’s data
recording for information sharing, knowledge building
and for crash reconstruction purposes;
Post-Crash Behavior: Process for how an HAV should
perform after a crash and how automation functions can
be restored;
Privacy: Privacy considerations and protections for users;
System Safety: Engineering safety practices to support
reasonable system safety;
Vehicle Cybersecurity: Approaches to guard against
vehicle hacking risks;
Human Machine Interface: Approaches for commu-
nicating information to the driver, occupant and other road
users;
Crashworthiness: Protection of occupants in crash situ-
ations;
Consumer Education and Training: Education and
training requirements for users of HAVs;
Ethical Considerations: How vehicles are programmed to
address conflict dilemmas on the road; and
Federal, State and Local Laws:
2. Model State Policy
It contains recommended policy areas for states to consider, with
a goal of generating a consistent national framework for the
testing and deployment of HAVs. States can set up the following
administrative structure and processes to administer requirements
regarding the use of public roads for HAV testing and
deployment in their states:
Application by manufacturers or other entities to test
HAVs on public roads;
Jurisdictional permission to test;
Testing by the manufacturer or other entities;
Drivers of deployed vehicles;
Registration and titling of deployed vehicles;
Law enforcement considerations; and
Liability and insurance.
The federal government is hoping that the states will adopt this
policy. It would avoid a patchwork of state laws.
3. Current Regulatory Tools of the Department of
Transportation (DOT) that can be used to accelerate the safe
development of HAVs. The federal government will explore how
the existing regulatory tools can be applied to the autonomous
driving (AD) development.
Interpretations;
Exemptions;
Rulemakings;
Enforcements.
4. Modern Regulatory Tools
Considered New Authorities
NHTSA is looking into new ways to regulate the AD development,
such as:
Safety Assurance: Pre-market testing, data and analyses to
DOT to demonstrate that organization’s design, manufac-
turing and testing processes apply NHTSA’s vehicle
performance guidance.
Pre-Market Approval: Pre-market approval authority, in
which the government inspects and affirmatively approves
new technologies, would be a departure from NHTSA’s
current self-certification system. The merits and
challenges of implementing some form of a pre-market
approval are discussed.
Cease and Desist: Require manufacturers to take
immediate action to mitigate safety risks that are so
serious and immediate that they constitute “imminent
hazards.”
Expanded Exemptions: Raising the cap on the number of
vehicles subject to exemption and/or the length of time of
exemptions, to facilitate the safe testing and introduction
of HAVs.
Post-sale Regulation of Software Changes: Regulate post-
sale software changes in HAVs.
Considered New Tools
Variable Test Procedures: Expand vehicle testing
methods to create test environments more reflecting real-
world environments.
Functional and System Safety: Make mandatory the 15-
point Safety Assessment envisioned in the first section
(Vehicle Performance Guidance).
Regular Reviews: Regular reviews of standards and
testing protocols to keep current with the development of
technology.
Additional Recordkeeping and Reporting: Require
additional reporting about HAV testing and deploy-ment.
Enhanced Data Collection: Enhance data recorders and
greater reporting requirements about the performance of
HAVs.
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... Also, in order to support stakeholders such as NRAs, OEMs, and service providers, the regulatory timing is vital and can affect the challenges and possibilities of the introduction of CAVs. It is therefore of importance that such stakeholders proactively engage with various consultations and policy development initiatives to ensure a regulatory framework that can address their interests and optimally balance risks against the benefits of CAVs (Baker et al. 2020;Ilková & Ilka, 2017). It should be noted that the terminology addressing the topic of connected and autonomous vehicles and the necessary infrastructure for its deployment could be somewhat confusing. ...
... Legal challenges of CAD in the area of administrative law include questions such as: Does CAD require a special driving license, are age requirements necessary for CAV users, where should CAD be allowed, should there be dedicated lanes for CAD, should all traffic rules be followed by CAVs and should there be any external indicator on the vehicle when in autonomous mode? (Ilková & Ilka, 2017). Civil law coverage related to CAVs and CAD consists of both civil liability and product liability challenges. ...
... Thus, corporate criminal responsibility and crimes against life and health needs consideration and review to fit in the CAD context. The protection of vehicle users against hacker attacks has a criminal aspect, to protect against cybercrime, but also an aspect of developing appropriate security systems regulated by standards and technical norms (Ilková & Ilka, 2017;Nynke, 2019;Glancy et al., 2016;Goldstein, 2017). 7 ...
Technical Report
Full-text available
Connected and Automated Driving (CAD) is an important area of digital technology that will bring disruption to individuals, economies, and societies. Most forms of CAD require some level of infrastructure support for their safe operation. Additional infrastructure and services to support CAD have the potential to improve safety even further, and to bring other benefits such as increased efficiency or reduced congestion. However, the infrastructure requirements from Original Equipment Manufacturer (OEMs) are not always clear, and it is difficult for National Road Authorities (NRAs) to predict and plan for the future levels of support needed for CAD given rapidly evolving technology and uncertain projections of future CAD demand. In addition, there is also a need for better dialogue among NRAs, OEMs and service providers to articulate those requirements and to define a roadmap and responsibilities for achieving safe and smart roads through CAD.
... Transport choice modeling is an approach applied to understand the travelers' behavior regarding the current situation and future scenarios, such as developing new roads or technology including the availability of autonomous vehicles (AVs) [1]. AVs are divided to 6 levels based on the Society of Automotive Engineers (SAE) and the National Highway Traffic Safety Administration (NHTSA) in the United States [2]. In this research, the AV is Level 5 in which the vehicle is fully autonomous and capable of performing all driving tasks under all conditions without any human involvement. ...
... Thus, conducting analytical study is applicable. The aims of this research are (1) to model multitasking on board of cars, AVs, and SAVs, (2) to find the factors that have the highest impact on the acceptability of SAVs and the possibility of multitasking, and (3) to evaluate the impacts of certain factors on the travel time. It is worth noting that this work is built on a work done by Hamadneh [29]. ...
... The Kaiser-Meyer-Olkin (KMO) test is applied to measure the adequacy of the sample size, and Bartlett's test is used for sphericity (i.e., significance at a confidence level of 95%) [80]. The KMO is 0.633 for Set (3) and 0.614 for Set (2), which are acceptable values (i.e., KMO>0.05). Thus, the sample size is large enough [80]. ...
Article
Full-text available
Travelers on board of transport modes conduct active and passive activities to mitigate the negative impact of traveling. Multitasking on board of conventional transport modes is studied by several researchers, but limited efforts are focusing on multitasking in case of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs). In this paper, the effects of multitasking on behavior of travelers on board of conventional cars (cars), AVs, and SAVs are analyzed. Furthermore, finding the impact of several factors on the travel time, the acceptability of SAVs, and conducting onboard activities are assessed. The study considers solely main trip purposes within urban areas. A stated preference (SP) survey is distributed in Budapest, Hungary, and 276 participants are collected. An SP includes discrete choice experiment (DCE) that is designed to mimic the realistic situation when AV is on the market. The DCE considers the attributes and attributes levels of the alternatives where rationality is maintained in the design. A transport mode choice model, which includes several variables influencing the choice of a transport mode, is developed. In addition, an SP includes Likert scale and sociodemographic sections. Likert scale and exploratory factor analysis (EPA) are used to understand the impact of some factors on the travel time, the acceptability of SAVs as transport modes, and conducting onboard activities. The multinomial logit (MNL) model is applied, where a transport mode choice model of cars, AVs, and SAVs is developed. The results of the developed model show that travelers are willing to choose AVs over cars, and SAVs over AVs. Moreover, travelers with high income are more willing to use AVs over SAVs and more likely to use cars than SAVs. Besides, people from the older age group prefer using SAVs more than other age groups. The results demonstrate the probability of selecting a transport mode with active activities on board is larger than the probability of choosing a transport mode with passive activities. Besides, the findings of EFA and Likert scale analyses demonstrate that the waiting time has the largest negative effect on the travel time, seat availability affects the conduction of onboard activities, and the internal design of SAVs influences the use of SAVs as transport modes. The results of current research can be beneficial to transport planners, transport operators, and vehicle manufacturers.
... It provides non-drivers with more autonomous mobility and has the potential to minimize drivers' chauffeuring duties and transit subsidy demands, particularly for the blind, intoxicated, elderly, underage, and impaired people [Hussain and Zeadally, 2018]. A driving test or driving license is no longer necessary since humans do not need to drive [Ilková and Ilka, 2017]. With fewer traffic accidents and collisions, autonomous vehicles can improve safety while also lowering crash risks and insurance costs. ...
... Furthermore, uncertainty about future regulations and policies may defer the deployment of driverless cars on the road [Saeed et al., 2016]. Transparent as well as unambiguous regulations and procedures that address potential consumers' concerns are essential [Ilková and Ilka, 2017]. Another important concern is how self-driving cars make a judgment with justifiable behaviors in potentially challenging emergencies [Hussain and Zeadally, 2018]. ...
Article
Full-text available
The deployment of autonomous vehicles has the potential to significantly lessen the variety of current harmful externalities, (such as accidents, traffic congestion, security, and environmental degradation), making autonomous vehicles an emerging topic of research. In this paper, a literature review of autonomous vehicle development has been conducted with a notable finding that autonomous vehicles will inevitably become an indispensable future greener solution. Subsequently, 5 different deep learning models, YOLOv5s, EfficientNet-B7, Xception, MobilenetV3, and InceptionV4, have been built and analyzed for 2-D object recognition in the navigation system. While testing on the BDD100K dataset, YOLOv5s and EfficientNet-B7 appear to be the two best models. Finally, this study has proposed Hessian, Laplacian, and Hessian-based Ridge Detection filtering techniques to optimize the performance of those 2 models. The results demonstrate that these filters could increase the mean average precision by up to 11.81%, and reduce detection time by up to 43.98% when applied to YOLOv5s and EfficientNet-B7 models. Overall, all the experiment results are promising and could be extended to other domains for semantic understanding of the environment. Additionally, various filtering algorithms for multiple object detection and classification could be applied to other areas. Different recommendations and future work have been clearly defined in this study.
... The autonomous driving context forces deep learning models to make critical decisions affecting the safety of their users, which makes it essential to consider legal aspects [3]. As such, the need to obtain explanations for the inferences performed by these models emerges. ...
Article
Full-text available
Deep learning has rapidly increased in popularity, leading to the development of perception solutions for autonomous driving. The latter field leverages techniques developed for computer vision in other domains for accomplishing perception tasks such as object detection. However, the black-box nature of deep neural models and the complexity of the autonomous driving context motivates the study of explainability in these models that perform perception tasks. Moreover, this work explores explainable AI techniques for the object detection task in the context of autonomous driving. An extensive and detailed comparison is carried out between gradient-based and perturbation-based methods (e.g., D-RISE). Moreover, several experimental setups are used with different backbone architectures and different datasets to observe the influence of these aspects in the explanations. All the techniques explored consist of saliency methods, making their interpretation and evaluation primarily visual. Nevertheless, numerical assessment methods are also used. Overall, D-RISE and guided backpropagation obtain more localized explanations. However, D-RISE highlights more meaningful regions, providing more human-understandable explanations. To the best of our knowledge, this is the first approach to obtaining explanations focusing on the regression of the bounding box coordinates.
... The following section describes the current status of legislation globally and discusses how different policies account for equity, safety, and liability concerns. In 2011, Nevada was the first U.S. state and first jurisdiction globally to authorize the operation of AVs on public roads (72). Since then, 15 states have enacted 18 AV bills, and 29 states have enacted AV-related legislation. ...
Technical Report
This technical report investigates the burgeoning field of Autonomous Vehicles (AVs), a transformative technology set to redefine transportation by enhancing safety, efficiency, and reducing human error. Despite their potential, AVs introduce complex challenges and safety concerns, particularly in urban environments. This study focuses on California from 2014 to 2022, offering a comprehensive examination of AV collision patterns, safety dynamics, and performance compared to Conventional Vehicles (CVs). Therefore, the objectives of this study are to (1) analyze trends in AV crashes to identify recurring patterns or anomalies that may indicate underlying issues or areas for improvement, (2) utilize the latest data sets to predict injury outcomes in AV crashes, aiming to understand the factors that contribute to the severity of injuries and (3) Identify critical determinants of AV crash injuries and conduct a detailed analysis to understand how these factors influence the nature and extent of injuries sustained. Employing a blend of descriptive and spatial analyses, the report delves into the specifics of AV collisions, revealing predominant crash types and significant spatial clusters in major urban centers. The research utilizes various machine learning algorithms to predict crash outcomes, pinpointing critical determinants like vehicle damage and manufacturer. It also assesses the impact of environmental and vehicular factors, such as lighting and weather conditions, on AV collisions. Through detailed scenario analysis, the report explores the diverse challenges AVs face, highlighting the importance of robust design and advanced safety features. The findings aim to inform stakeholders, including manufacturers, policymakers, and urban planners, about the key areas for improvement and collaboration. As AVs continue to evolve, this report underscores the necessity of ongoing research, technological advancements, and strategic planning to ensure their safe and effective integration into the transportation ecosystem.
... The irruption of autonomous vehicles poses regulatory and insurance challenges that must be addressed with care and that are already being studied by the scientific community. Thus, in [23], the importance of establishing clear rules is highlighted, proposing approaches such as mandatory insurance under strict liability. This work underlines the need for collaboration between legislators and technicians. ...
Article
Full-text available
This article delves into the acceptance of autonomous driving within society and its implications for the automotive insurance sector. The research encompasses two different studies conducted with meticulous analysis. The first study involves over 600 participants involved with the automotive industry who have not yet had the opportunity to experience autonomous driving technology. It primarily centers on the adaptation of insurance products to align with the imminent implementation of this technology. The second study is directed at individuals who have had the opportunity to test an autonomous driving platform first-hand. Specifically, it examines users’ experiences after conducting test drives on public roads using an autonomous research platform jointly developed by MAPFRE, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid. The study conducted demonstrates that the user acceptance of autonomous driving technology significantly increases after firsthand experience with a real autonomous car. This finding underscores the importance of bringing autonomous driving technology closer to end-users in order to improve societal perception. Furthermore, the results provide valuable insights for industry stakeholders seeking to navigate the market as autonomous driving technology slowly becomes an integral part of commercial vehicles. The findings reveal that a substantial majority (96% of the surveyed individuals) believe that autonomous vehicles will still require insurance. Additionally, 90% of respondents express the opinion that policies for autonomous vehicles should be as affordable or even cheaper than those for traditional vehicles. This suggests that people may not be fully aware of the significant costs associated with the systems enabling autonomous driving when considering their insurance needs, which puts the spotlight back on the importance of bringing this technology closer to the general public.
Article
Full-text available
Autonomous vehicles (AVs) represent a potentially disruptive yet beneficial change to our transportation system. This new technology has the potential to impact vehicle safety, congestion, and travel behavior. All told, major social AV impacts in the form of crash savings, travel time reduction, fuel efficiency and parking benefits are estimated to approach $2000 to per year per AV, and may eventually approach nearly $4000 when comprehensive crash costs are accounted for. Yet barriers to implementation and mass-market penetration remain. Initial costs will likely be unaffordable. Licensing and testing standards in the U.S. are being developed at the state level, rather than nationally, which may lead to inconsistencies across states. Liability details remain undefined, security concerns linger, and without new privacy standards, a default lack of privacy for personal travel may become the norm. The impacts and interactions with other components of the transportation system, as well as implementation details, remain uncertain. To address these concerns, the federal government should expand research in these areas and create a nationally recognized licensing framework for AVs, determining appropriate standards for liability, security, and data privacy.
Article
This special issue includes research articles which apply spoken language processing to robots that interact with human users through speech, possibly combined with other modalities. Robots that can listen to human speech, understand it, interact according to the conveyed meaning, and respond represent major research and technological challenges. Their common aim is to equip robots with natural interaction abilities. However, robotics and spoken language processing are areas that are typically studied within their respective communities with limited communication across disciplinary boundaries. The articles in this special issue represent examples that address the need for an increased multidisciplinary exchange of ideas.
Autonomous cars -initial thoughts about reforming the liability regime
  • M N Schubert
M. N. Schubert, "Autonomous cars -initial thoughts about reforming the liability regime", Gen Re Insurance Issues, Cologne, 2015.
Autonomous cars and the law
  • E Hilgendorf
E. Hilgendorf, "Autonomous cars and the law," http://cgd.swissre.com/ global_dialogue/topics/Autonomous_cars/
Ten ways autonomous driving could redefine the automotive world
  • M Bertoncello
  • D Wee
M. Bertoncello, D. Wee, "Ten ways autonomous driving could redefine the automotive world," McKinsey & Company, 2015.
Federal Automated Vehicles Policy Accelerating the Next Revolution in Roadway Safety
"Federal Automated Vehicles Policy. Accelerating the Next Revolution in Roadway Safety," U.S. Department of Transportation-National Highway Traffic Safety Administration, USA, September 2016.
Sue My Car Not Me: Products Liability and Accidents Involving Autonomous Vehicles
  • J K Gurney
J. K. Gurney, "Sue My Car Not Me: Products Liability and Accidents Involving Autonomous Vehicles," Journal of Law, Technology & Policy, vol. 2013, no. 2, 2013 pp. 247-277.