, and the community needed us for some activities.”
Officials said the rain actually makes good conditions for their Aug. 30 Demo Derby, which started at 7:30 p.m. The Kids Power Wheels Demo Derby started at 7 p.m. A complete list of events for the Barbour County Fair can be found here, under the “schedule” tab.
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The FISITA Automotive HMI Online Conference was moderated by Christophe Aufrère, CTO of Faurecia, with speakers Bryan Reimer from the MIT Center for Transportation and Logistics, Philipp Kemmler-Erdmannsdorffer from NIO, and Omar Ben Abdelaziz from Faurecia.
The following transcript is taken from the presentation by Bryan Reimer of MIT on What Do Production ADAS and ADS Systems Tell Us About the Migration to Collaborative Driving.
Christophe: Now let me introduce the first speaker. The first speaker is Bryan Reimer, who is a brilliant research scientist in the MIT Center for Transportation and Logistics, which aims to find solutions for the next generations of human factor changes. He also founded and leads the Advanced Vehicle Technology Consortium and he got also different innovation awards so now the floor is Bryan's. Thank you Bryan, and good luck with your presentation.
Bryan: Thank you for the introduction and I hope that everybody is in good health and safe in these turbulent times. I'd like to talk a little today about what production advanced driver assistance systems and automated driving systems are telling us about the migration forward on our path of automation towards one that I would consider of collaborative driving versus autonomous driving.
Most importantly I think that we need to look back for a moment. The history of our pursuit of driverless technologies is not new. All the way back in 1926, in the context of remote control, the Milwaukee Sentinel in the U.S. documents the first move towards driverless vehicles. In the 1950s, GM invested copiously in this topic. In the 1980s several prototypes. The modern era of driverless and automated technologies really was kicked off with the DARPA challenges in the 2000s and the introduction of the Google self-driving car program just over ten years ago. In the ten years since, we've invested countless billions of dollars in the pursuit of this technological marvel. What's next? I'd argue it's a drastic shift in how we live and move, but it is one that will not clearly take the driver out of the driver's seat anywhere as quickly as the forecasts five or ten years ago may have presumed.
When we think to the context of what autonomy means to different people, there are a number of different viewpoints in this topic. As I highlighted in a piece that's in my Forbes blog in 2018 we haven't yet begun to agree on what are we trying to achieve here. Are we trying to achieve vehicles and vehicle systems that just encompass hands-free driving - many of the vehicle systems that are being produced today. Or are we really looking for Robo taxis, autonomous mobility, on-demand services, with or without safety drivers. Delivering packages or moving people in a neighbourhood or city. A mobility ecosystem that provides seamless intermodal connectivity, moving people from home to the subway or steel-on- steel rail that is far more efficient or - most importantly as I would think of it - how do we begin to target a safety threshold that moves us towards the context of vision zero? Because living and moving safely is perhaps the ultimate target we should be looking to achieve. Now obviously there's different elements of the mobility ecosystem trying to pursue all of these components. These are big complex problems in and of themselves. How do we begin to target where are we trying to achieve success so that we can find a successful end game in the quest for mobility?
The hard part here is that we as drivers - humans sitting behind the steering wheel - have a really difficult time understanding the human-machine characteristics of what our new role may be. As humans we're really attuned to understanding: are we driving, or are we riding? Am I responsible for the operation of this vehicle or am I a passenger in the vehicle along for the ride? Now, as we automate more, we move forward in our pursuit of collaborative driving, we are going to need to define some middle points here where driving doesn't necessarily mean driving the traditional way. However, we need to educate the populace well beyond SAE 3016 to understand what an individual's role may be at any given point in time and it very much is the human machine interface that is critical to providing that context understanding and it is an understanding I will discuss in a moment here around data and why that understanding is difficult today. It needs to be iterated forward over time if we are going to successfully deploy all the technologies we are working on. So how do we move people from understanding the foundations: from traditional driving, to modern driving, and how riding may very well be different.
So, about five years ago, I led the development of the Advanced Vehicle Technologies Consortium to focus on collecting and analyzing data on how people are touching advanced driver assistance systems and other higher levels of automation in production systems in the field. So how do we get an understanding of system use? How drivers are adapting to use systems, or not so, so that we can understand how they are behaving and begin to iterate designs of HMIs and the driver technology interaction dynamic that is happening on the roads forward faster. In essence, how do we get the industry to collaborate more strategically; learn from data, learn from each other so that we can engineer systems more effectively over time. The consortium is now supported by four OEMs, several suppliers, insurers, leading technology companies such as Google, and some of the key safety stakeholders throughout the world including HIS, JD Powers, Consumer Reports, working together collaboratively to try to understand the complexities of system design development on our roads. So let's dive into a little of the data for a moment.
Most importantly, and I'm going to switch over to the complexity of video today. Hopefully you can watch this clip. Let's cross now.
The largest supplier of production level automated driving systems is clearly Tesla at this point with a number of traditional OEMs quickly moving behind, but it's very much not the automation that Tesla is providing - and I'll play that clip again - that's the issue it's very much the interface to that automation. By any count, autopilot is a sufficiently flawed automation system. It's not perfect. It cannot drive autonomously. It cannot handle the complex cut in the construction zone in this video. It's not expected to, but how do we ensure that the driver of that system understands that, is ready to take over - attentive to the situation around them, not fixated on doing things in the vehicle - to ensure that we are developing a mobility framework enhanced in safety? Unfortunately, the complex designing of appropriate technology and deployments in the car is incredibly complex. It's difficult to understand how people are going to use, not use, appropriately trust, and inappropriately trust technology on their own. It's no myth that with automation comes a responsibility for enhanced education. The aviation community has known that for decades.
So when I look at other vehicles we're studying – Cadillac’s Super Cruise for example - we see in this video clip right here a driver's first experience with Super Cruise: an automation technology that may very well be stronger than autopilot from an automation perspective, but it's far more advanced from an interface perspective. I'll repeat that again so Super Cruise - while many think of it as an automated driving system - is really a system designed around perhaps one of the strongest HMIs developed to date in the vehicle. Lead researcher on it Chuck Green works part-time with us now. Retired from GM not so long ago. The behavioural adaption system in Super Cruise is very unique. The system in particular is designed around an attention management strategy that is coupled with the automated driving system, so I think that is very important to understand. Literally building the automation path planning control to work coherently with the attention management system.
So we begin to think about a transition and pathway to appropriate use. How people move from Level 0, manual control, to Level 1 ACC (Adaptive Cruise Control) and over to Super Cruise Level 2, we see that Level 1 plays a very important role in how people learn about the technology; how they transition to the Level 2 state; and how they transition back; and that interfaces, in particular, if developed to support driver attention, to motivate drivers, can be used cohesively to include them in that collaborative relationship and promote appropriate uses of the technology. I'm not saying that any development today is perfect. I'm not saying that the second or third generation of Super Cruise that that many are working on beyond GM won't be better than the first. I'm just saying that the unique characteristics of this system as it's designed are quite effective in promoting the appropriate use of the technology. So let's look at two specific components of this in video in particular.
So let's call it, it's designated the blue state, or the manual override state. In this case when the driver here decides that they're going to change lanes, the automation is overridden