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 Where these maps may be out of date, they would need to be able to fall back to reasonable behaviors,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.