Potential limits or obstacles
The sort of hoped-for potential benefits from increased vehicle
automation described may be limited by foreseeable challenges, such as
disputes over liability (will each company operating a vehicle accept
that they are its “driver” and thus responsible for what their car
does, or will some try to project this liability onto others who are not
in control?), the time needed to turn over the existing stock of
vehicles from non-automated to automated, and thus a long period of
humans and autonomous vehicles sharing the roads, resistance by
individuals to having to forfeit control of their cars, concerns about
the safety of driverless in practice, and the implementation of a legal
framework and consistent global government regulations for self-driving
cars. Other obstacles could include de-skilling and lower levels of
driver experience for dealing with potentially dangerous situations and
anomalies, ethical problems where an automated vehicle’s software is
forced during an unavoidable crash to choose between multiple harmful
courses of action (’the trolley problem’), concerns about making large
numbers of people currently employed as drivers unemployed (at the same
time as many other alternate blue collar occupations may be undermined
by automation), the potential for more intrusive mass surveillance of
location, association and travel as a result of police and intelligence
agency access to large data sets generated by sensors and
pattern-recognition AI (making anonymous travel difficult), and possibly
insufficient understanding of verbal sounds, gestures and non-verbal
cues by police, other drivers or pedestrians.
Possible technological obstacles for automated cars are:
artificial Intelligence is still not able to function properly in
chaotic inner-city environments,
a car’s computer could potentially be compromised, as could a
communication system between cars,
susceptibility of the car’s sensing and navigation systems to different
types of weather (such as snow) or deliberate interference, including
jamming and spoofing,
avoidance of large animals requires recognition and tracking, and Volvo
found that software suited to caribou, deer, and elk was ineffective
with kangaroos,
autonomous cars may require very high-quality specialized maps to
operate properly. Where these maps may be out of date, they would need
to be able to fall back to reasonable behaviors,
competition for the radio spectrum desired for the car’s communication,
field programmability for the systems will require careful evaluation of
product development and the component supply chain,
current road infrastructure may need changes for automated cars to
function optimally,
discrepancy between peopleís beliefs of the necessary government
intervention may cause a delay in accepting automated cars on the road.
Whether the public desires no change in existing laws, federal
regulation, or another solution; the framework of regulation will likely
result in differences of opinion,
employment - Companies working on the technology have an increasing
recruitment problem in that the available talent pool has not grown with
demand. As such, education and training by third party organizations
such as providers of online courses and self-taught community-driven
projects such as DIY Robocars and Formula Pi have quickly grown in
popularity, while university level extra-curricular programmers such as
Formula Student Driverless have bolstered graduate experience. Industry
is steadily increasing freely available information sources, such as
code, datasets and glossaries to widen the recruitment pool.