IEEE Consumer Electronics Magazine - October 2015 - 104

intersecting sets of information for two adjacent vehicles, but
these are unlikely to be identical.

COEXISTING MANUALLY DRIVEN TRAFFIC
AND AUTOMATED CARS
A global network of vehicles is forming, with drivers and
vehicles communicating and exchanging information [20]
through services including global positioning systems,
weather, and traffic monitoring in addition to the ad hoc networks established directly by drivers and passengers through
calls, texts, and apps via their mobile devices. If we consider
the upward trend in deployed sensors/actuators and available
processing power and communication bandwidth, the next
logical requirement will be to integrate semiautomated vehicles (initially at a low penetration rate), yielding a network of
coexisting manually driven cars and self-driving vehicles.

Ethically driven principles must
be built into automated vehicle
algorithms that determine how
scenarios would be ranked
and retrieved in various
critical driving situations.
Reconciling multiplexity in this context is a challenge as
the road of the near, distant, and far future will be driven by
heterogeneity and diversity within and between vehicles. Not
only is the information available to each vehicle different,
automated cars from different manufacturers will be based on
different algorithms and thus behave differently with regard
to each other and to the road [3], [6]. Understanding vehicle
diversity and the resultant heterogeneity of behavior on the
road is a crucial step toward developing solutions that will
avoid problematic hazards such as evaluating traffic situations and selecting options for controlled movement [3], [6].
Many companies in the transportation industry are investing enormous financial resources to ensure that semiautomated, self-driving, or even fully automated cars can function in
isolated settings. Even if much of the coverage of this exercise is actually speculative and hyped, we can expect an
increasing level of automated driving in the coming years in
ordinary traffic. Thus, for a long time to come, people will be
faced with mixed traffic scenarios and the question of how to
integrate nonconnected, manually steered, semiautomated,
and fully automated vehicles into traffic flow worldwide.

COOPERATION AND SOCIAL BEHAVIOR
The increasing capacity to enable different levels of automated
driving [15], combined with the forecast problem of coexisting
automated and manually driven vehicles together with VRUs
104 IEEE ConsumEr ElECtronICs magazInE

^

october 2015

(pedestrians, bicyclists, wheelchair users, etc.), raises the issue
of efficient cooperation between all road users to guarantee safe
coexistence as well as to enable efficient behavior and maintain
driving performance for those in vehicles on the road. One of the
biggest challenges in the mixture of traffic entities lies in the
unpredictability of humans in taking agency (free choice from
the range of available options) on the road as well as the unlikely
prospect of the authors of algorithms to have considered all necessary options and actions of application and instructions interpreted by humans or other agents, such as the "thing agents"
described in [6]. This unpredictability makes it impossible to
guarantee safe and accident-free travel for all persons at all times
even for the best and most sophisticated automated cars. As long
as there are pedestrians or other VRUs in the system, vehicles
that are not automated, and computer programs with errors, the
cooperation of those participating in traffic will be subject to the
agency of humans and the errors of automation. Even in the
most fail-safe and secure systems, human creativity will find
ways to intentionally discover workarounds within systems to
meet their own needs, while machines will run programs that
have unexpected outcomes when interpreted by humans and
contribute to conflict [4], [5].
For the vehicle transportation system to work, all road
users, whether human or mechanized, must engage in cooperation within the car (i.e., between the automation and its driver),
with other road users, with any external agents to the car
(human or automated), and with traffic/intelligent transportation systems (ITS) infrastructure [3], [6], [22]. To achieve this,
some agency (free will to choose) on the part of all parties
must be yielded to others within the system at various times to
negotiate successful participation within the system. It is
unwise to assume that nonautomated drivers will be expected
to yield to fledgling semiautomated or automated vehicles as a
matter of course. This would create an unbalanced system by
which human drivers would have cognitive load increased as
they take on the additional labor of "babysitting" semiautomated and automated vehicles on the roads, enabling those manufacturers to claim successes that would be due, in part, to
human drivers enabling their success [3], [6], [20]. This could
lead to accidents in situations when humans selectively (rather
than always) assist automation on the road by yielding [4], [5].

ETHICAL ISSUES ABOUND
In a critical situation, an automated car may have to decide
between crashing into a group of pedestrians crossing the
road (who have taken agency by not looking before crossing)
or crashing itself (with its passengers) into an obstacle (such
as another car, public transit, house, or wall), risking injury
and/or death of its passengers. Ethically driven principles
must be built into automated vehicle algorithms that determine how scenarios would be ranked and retrieved in various
critical driving situations. Would an automated vehicle have
primary loyalty to its owner or a broader ethical outlook to
protect society in general? Will the hierarchy need to be legislated to avoid ownership bias? Ideally, automated vehicles
should be able to detect upcoming situations in advance,



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