3. Autonomous vehicles,
BleuTech in its announcement of their new (mini) smart city construction (starting December 2019), BleuTechPark, in the Las Vegas Valley have indicated the intention of using self-driving vehicles for public transportation. They are not alone.
It is now quite a few decades since the first automated metro entered into service (Victoria Line, London 1967 -but a driver was seated in the cabin, just in case). The longest fully automated metro system, today, is operating in Singapore (it has a GoA4 automation level – the train runs with no operator on board, it is able to detect obstacles on the line and manage emergency situation).
Metro systems are basically closed systems, they run on rails and everything can be controlled (including the presence of passengers that cannot cross the rails).
Masdar, in the UAE, is an example of a smart city labs where public transportation uses autonomous vehicles, see photo – watch the clip. The system requires more sophistication because the circulation is not happening in a protected area, although all vehicles operation occurs in a reserved “underground layer”, hence the overall environment is more predictable. Besides, there is a good coordination among the vehicles and the road infrastructure greatly simplifying automation.
Interesting to notice that there are basically two paradigms being investigated and experimented. One that is tying the road infrastructure with the autonomous vehicles (and 5G according to some can provide the connectivity layer, with low latency, required to connect vehicles among them and with the infrastructure), the other is assuming that vehicles are completely autonomous, they do not need to interact with each other nor with the infrastructure.
Clearly, the second paradigm is the one that can ensure the viability of an autonomous vehicle everywhere, the first one is more effective if we are considering an environment like the one we can expect in 30 years time, where every vehicle is connected and autonomous because it would be safer and cheaper. The problem is that this approach is not effective in the transition period and autonomous vehicles manufacturers cannot wait for it if they want to sell their product now (and over the coming 20-30 years). On the other hand, it would be outrageously expensive for a municipality to create a fully supporting infrastructure at a time when most vehicles are NOT autonomous and would not take advantage of the infrastructure support (it is the usual chicken and egg problem).
On the other hand, if you are designing a city from scratch, as it is the plan of BleuTech Park, it makes sense to design it planning for a road infrastructure that can be future proof.
Here again one has to be careful: technology is evolving fast and even if a technology today can be future proof in terms of basic -needed- functionality it may not be future proof in terms of compatibility and of economics.
This is where the Digital Transformation kicks in. You design only the very basic hardware and move most of the functionality to software since software it’s so much easier to upgrade than hardware.
In the case of road infrastructure the basic technology is “sensors”. You deploy as many sensors as you can as you build the road infrastructure (at this time it is reasonably cheap to embed sensors) and you harvest the data on open platforms. These platforms are the one to support future applications that will be able to grow and change as the overall context evolve (including the evolution of autonomous vehicles). Data are providing the “food” needed to artificial intelligence based processing to deliver today’s and tomorrow services.
This, as far as I can understand, is the approach chosen by BlueTech Park for intelligent transportation.