6 minutes
Challenges of fully autonomous driving
From Level 4 and onwards, we can face challenges in the adoption of autonomous driving technology. These can be classified into (1) Legal challenges, (2) Certification and intellectual property, (3) Ethical challenges, (4) Social challenges.
Legal challenges
We can note two cases in which society should adapt to this innovation. In the first case, if we apply autonomous driving to trucks to make the transportation of goods more cost-efficient, it will be natural to cross the country’s borders.
In that case, the different legislations should have a common ground so that a truck certified to operate autonomously in country A should be allowed to do so in country B.
A second case is a liability in case of an accident. Up to and including Level 3, the driver is required to maintain or acquire control of the car in all moments, so the current legislation which makes liable the human driver is enough, but in Level 4, the system should inform the driver with enough time to regain the control of the car, is the conditions for autonomous driving are not met anymore.
In this case, it will be challenging to establish without doubt the driver’s liability or the system if an accident is to happen during the transition. A certified black box installed by a third party could be a possible solution, although this will increase the car’s final cost. (Douma & Palodichuk, 2012)
Certification challenges and intellectual property
An autonomous driving device that can be liable will be required to meet severe governmental certifications to be allowed to operate.
During those certifications, sensitive information about the technology behind the system can be required to be shared with the authorities. The challenge is how to share such information with countries that have been proven to be unfriendly regarding foreign countries’ intellectual property.
In such a case, a decision should be made regarding the risk of losing trade secrets or market share.
Ethical challenges
Costa (1986) analyses a thought experiment called the trolley problem. In a nutshell, the dilemma is:
There is a runaway trolley barreling down the railway tracks. Ahead, on the tracks, there are five people tied up and unable to move. The trolley is headed straight for them. You are standing some distance off in the train yard, next to a lever. If you pull this lever, the trolley will switch to a different set of tracks. However, you notice that there is one person on the sidetrack. You have two options:
- (1) Do nothing, and the trolley kills the five people on the main track.
- (2) Pull the lever, diverting the trolley onto the side track where it will kill one person. Which is the most ethical choice?
This problem can be translated in the case of autonomous driving, as follows: the person with the lever control is the artificial intelligence, the innocent bystander can be the person inside the car or a pedestrian, and the five people in the way of the train a bus full of people on a collision course with the autonomous vehicle. Should the autonomous car sacrifice the life of its occupants or a pedestrian for the greater good?
The solution to that dilemma will have a considerable impact on:
- (a) Legal: If a car, to prevent a collision with a bus full of people, decides to switch the path, killing a pedestrian, will the manufacturer of the system is liable for that death?
- (b) Marketing: If the materialistic solution is adopted, the car will decide for the smaller number of casualties. Are you going to rely on a system that may choose to sacrifice you for the greater good?
Social challenges
Even though not directly related to the innovation itself, the adoption of autonomous driving will require governmental help regarding law changes and investment in new systems to make collaborative driving a reality.
Asking for help could be met with some lack of collaboration, as autonomous driving will affect a considerable segment of the population, such as taxi, bus and truck drivers.
To solve that problem, industry and government should work together to provide solutions to that problem, such as aid to reconversion programs and minimize the social disturbance such as unemployment that this innovation will cause.
Even though the challenges faced by the autonomous driving endeavour, the use of the Open Innovation (Savory, 2016a) approach, with several independents companies (with ties to several car manufacturers and not only one) developing different solutions to the problem, and with car manufacturers acting as integrators and financing several approaches to develop the technology, give the idea that the project can be completed in a reasonable amount of time, and that an internal change of goals in one integrator, will not affect the overall research and development.
It should also be noted how this approach uses technology transfer (Savory, 2016b) between all companies. For example, the sensors (camera, laser, radar, etc.) and actuators (interface to accelerate, brake, change gear) are controlled by the integrators (car manufacturers) that will share their technology and trade secrets, after signing a non-disclosure agreement, with companies to develop the autonomous driving algorithms. The algorithms can be commercialized as a license of use to the integrator or could be sold completely.
As software without maintenance can become quickly useless, a knowledge transfer should be in place in case of a property change of the algorithm. A contract of use for part of the integrator could avoid this problem.
References
- Costa, M. J. (1986). The Trolley Problem Revisited. The Southern Journal of Philosophy, 24(4), 437–449. https://doi.org/10.1111/j.2041-6962.1986.tb01581.x
- Douma, F., & Palodichuk, S. A. (2012). Criminal liability issues created by autonomous vehicles. Santa Clara Law Review, 52(4), 1157–1169. Retrieved from http://heinonline.org.libezproxy.open.ac.uk/HOL/Page?handle=hein.journals/saclr52&id=1213&div=37&collection=journals
- Horrocks, I., & Walker, S. (2016). Block 1 Technology, Innovation and Management (WEB033868). The Open University.
- Kate Bergman. (n.d.). Boeing Sees Greatest Demand for Pilots, Technicians in Asia Pacific Region - September 10, 2015. Retrieved January 8, 2017, from http://boeing.mediaroom.com/2015-09-10-Boeing-Sees-Greatest-Demand-for-Pilots-Technicians-in-Asia-Pacific-Region
- Phaal, R. (2004). Technology road mapping - A planning framework for evolution and revolution. Technological Forecasting and Social Change, 71(1–2), 5–26. https://doi.org/10.1016/S0040-1625(03)00072-6
- SAE International. (, 2014). Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems. SAE International, J3016, 1–12. Retrieved from http://standards.sae.org/j3016_201609/
- Savory, C. (2016a). Block 2 Open Innovation. The Open University.
- Savory, C. (2016b). Block 3 Technology Transfer: Building Value. The Open University.
- Vahidi, A., & Eskandarian, A. (2003). Research advances in intelligent collision avoidance and adaptive cruise control. IEEE Transactions on Intelligent Transportation Systems, 4(3), 143–153. https://doi.org/10.1109/TITS.2003.821292