Self-driving automobiles, Part Deux
In part two of this blog series, I want to explore the enabling factors for the self-driving automobiles along with adoption of this technology. It strikes a chord with the discussions in class about the adoption of technology and digital divide.
The necessity of self-driving automobile as mentioned in the last post is increasing because of chaotic traffic conditions, people spending time searching for parking and change in the mind-set of drivers — as more “digital natives” start driving.
Although self-driving automation appears to be a revolutionary technology, it is evolutionary as it requires the convergence of several technologies. In terms of technology, the convergence of machine learning, rise of connected-vehicle communications and sensors like LIDAR (Light Detection and Ranging), which can avoid collision and help with traffic management are really essential.
As it is a race for different companies to prove their technology and get to market first, it is possible to have vehicles operate on disparate technologies.
Even if we don’t include the legislative and infrastructure requirements of nations, which is essential for it to come into effect, the timelines for mass adoption looks around 10 years or even later if you consider worldwide adoption rather than next few years.
Initially, the implementation might be in confined areas and slowly as the confidence grows countries might have dedicated lanes on motorways for self-driving vehicles. The technology will have maximum impact only when used for public-transportation and not just private use.
For example, Easymile’s EZ10, a 12 seater driverless shuttle have been in operation in various parts of Europe. Now they are adopted in Singapore and Japan. These shuttles don’t have a steering wheel and can be used within confined areas in a pre-programmed route such as airports, university campuses, retirement centers and train stations.
In terms of adoption it appears that only the developed and mature economies will be the ‘early adopters’ and will slowly gain adopted in high growth economies. Although the self-driving automobiles can have bigger impact on high growth economies in terms of scale, the necessary infrastructure and enforcement of road rules are lacking.
Another practical challenge for high growth economies such as India and China is urbanization forces these countries to rethink their infrastructure. As the volume of people who migrate from villages to cities will be unprecedented, they need to improve the safety, quality and efficiency of public transport.
A proportionate increase of cars on the road will not be a viable option for these countries. It will be interesting to see the approach companies take to enter this market, especially India, due to lack of infrastructure as we saw in Week 4’s reading.
As noted by couple of other blogs, the increase of sharing economy might provide a plausible alternative to tackle these challenges. Another interesting blog by Raman Kaur discusses the “Smart nation” initiative by Singapore which is quite relevant to this topic.
Singapore has high population density and suffers from the perils of ownership of cars. With limited land space, one of their goal is to increase mobility by restricting personal ownership of the cars. Since 2015, they have opened up more than six kilometers of public roads for autonomous vehicle trials.
So, where does New Zealand stand in adoption of Self-driving automobile. As we discussed in the class, New Zealand is not an early adopter of technology. According to Ministry of transport “The Government has not yet received any formal requests to test autonomous vehicles in New Zealand on public roads”.
Perhaps, New Zealand could look at countries like Singapore and UK who are proactive and work with companies to test this technology.
