Self-Driving Vehicles: The Race to Get Them on the Road

Here are some highlights of the views of speakers represented in the podcast:

  • The introduction of the technological evolution and change that’s happening with autonomy have brought down barriers to entry. It’s allowed new players to come into the autonomous vehicle arena.
  • Cyber security across the entire industrial world is a huge question. There are so many vulnerabilities and that’s an area where Silicon Valley needs to be cognizant of partnering with government.
  • Some people think by 2020 we’re going to have fully autonomous vehicles, and some think it will happen in 2037. The entire business model is going to be shifting and we’re not sure when, we’re not sure how, but automakers may need to have a lot of cash on their balance sheets to make the transition to whatever the new mobility models are.

The full transcript of the podcast follows.

Host/Richard Banks: Hello and welcome to Talking Markets with Franklin Templeton Investments: exclusive and unique insights from Franklin Templeton.

I’m your host, Richard Banks.

Ahead on this episode, we continue the conversation from a previous episode on the future of self-driving vehicles, and the race to get them on the road.

Host/Richard Banks: Franklin Templeton’s James Cross leads the discussion with analysts Aleck Beach, Bobby Stevenson and Robert Rendler.

James: I thought we would just kind of start at the very beginning. What are the advancements or what are the enablers that allow us to talk about mass adoption of autonomous ability?

Bobby: Well, I think the first thing, obviously, is computing power, right? So, there was no ability 20 years ago to crunch the amount of data that’s coming into these cars. That data is coming in from suites of sensors that either didn’t exist 20 years ago or didn’t exist in sort of a form that was applicable to autos. So you have this sort of sensor suite. You’ve got a camera, a LIDAR [Light Detection and Ranging] sensor, a radar sensor and an ultrasonic sensor, so ultrasonic sensors are probably first. That’s the little beeping parking sensor on your car when you’re about to hit something. Cameras came next and were initially used to sort of emergency brake or warn you that you should be emergency braking the vehicle. Radar was sort of an early application of sort of that cruise control that sort of controls the distance between you and your car, the car in front of you. LIDAR is relatively new and is the highest-cost sensor and over 50 companies are trying to get the cost of that sensor down to something that can be deployed in an automotive application. So I think it’s, you know, the sensors either are being invented or reaching a state where they were cost-effective to be on a car and then getting the computing power together that can crunch all that data coming in.

Aleck: Maybe just to add, the mapping advancements that have come along. Not just to run the GPS navigation within your car from getting from point A to Point B, but as well, what is sort of a sense of a level of redundancy to some of the autonomous driving capability in terms of taking all that sensor data that’s coming in to the car and then helping the car through redundancy of mapping to create a perception of where it is, where it needs to go, and make decisions about how to get from point A to point B. So much more than just navigation for us, but the mapping that’s a pretty key feature that’s sort of more recent development.

James: Robert, same question on batteries. Why are we at the point where we can consider mass adoption of electrification?

Robert: The advancements on the battery chemistry have been pretty phenomenal. I mean, if we were to think about this, you know, 10 years ago, if you were to want a battery for the current Tesla Model 3, the costs were prohibitive. As that industry started to scale, you know, we’ve seen the costs come down, and, as we hear, an electric vehicle is a lot better enabler for autonomous vehicles. So, that kind of feeds into that loop also.