{"id":160162,"date":"2020-08-26T05:01:00","date_gmt":"2020-08-26T09:01:00","guid":{"rendered":"https:\/\/www.automoblog.com\/\/?p=160162"},"modified":"2023-11-06T16:41:31","modified_gmt":"2023-11-06T21:41:31","slug":"autonomous-cars-cognitive-brain-science","status":"publish","type":"post","link":"https:\/\/www.automoblog.com\/autonomous-cars-cognitive-brain-science\/","title":{"rendered":"Autonomous Cars & Cognitive Brain Science: Is There a Missing Link?"},"content":{"rendered":"\n
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This article originally appeared on AutoVision News<\/a>. It has been republished with permission. <\/em><\/p>\n\n\n\n

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\u201cConsider the hallmarks of human intelligence,\u201d writes Dr. M\u00f3nica L\u00f3pez-Gonz\u00e1lez in\u00a0her whitepaper<\/a>\u00a0published by the Society for Imaging Science and Technology. \u201cOvercome by computers in speed, accuracy, and precision, we continue to surpass computers in our capacity to generalize, learn, and manipulate and integrate multiple streams of known and novel information. Zooming into the issue of data efficiency, one of the biggest challenges in Cognitive Science is modeling how our minds do so much cognitively despite minimal amounts of information.\u201d\u00a0<\/p>\n\n\n\n

Or, as Dr. L\u00f3pez-Gonz\u00e1lez will often say in her presentations: humans are very good at improvising. \u201cSo how is it that we humans improvise? What allows us to improvise so successfully in an environment,\u201d she continued. \u201cIf we can understand the nitty-gritty of what\u2019s involved in motion, knowledge, and information, then we can create a mathematical system that can mimic that.\u201d<\/p>\n\n\n\n

Dr. L\u00f3pez-Gonz\u00e1lez, CEO and Chief Scientific Officer of La Petite Noiseuse Productions is a cognitive brain scientist and linguist by training. \u201cI\u2019m really interested in the big question of human intelligence,\u201d she explained. \u201cAnd by human intelligence, I mean all the aspects involved in how and why we\u2019re capable of maneuvering and surviving in the world or exacting change in the world.\u201d<\/p>\n\n\n\n

Examining The Checklist<\/h2>\n\n\n\n

The arrival of autonomous cars will enact a change in our world. Some changes may be harder to quantify at this exact moment, such as how the advent of self-driving cars will ultimately impact national infrastructure, local economies, or the legal system. Other changes seem more manageable to grasp right now, like how the current advancements in mobility are leading to a future with fewer fatal traffic accidents. Suffice it to say, as we move up through the SAE levels of automation<\/a>, our world will change.<\/p>\n\n\n\n

Perhaps a good strategy is to examine a change most everyone can universally agree on: that if self-driving cars (or even next-gen ADAS<\/a> technology) could reduce fatal traffic accidents, that would be a good thing. With that goal in mind, maybe the best course of action is something the autonomous vehicle<\/a> community is already quite good at doing: examining the capabilities of current technology and setting new benchmarks to achieve higher levels of performance.<\/p>\n\n\n\n

The level of openness and willingness to collaborate in the self-driving car industry is tremendous. Companies continue to work together to deploy new mobility solutions. Consumer advocacy organizations are calling for more precise guidelines<\/a> and definitions. The industry\u2019s top conferences have moved to virtual platforms to accommodate the engineering community during COVID-19. Despite the uncertainty of the pandemic, good things continue to materialize in the way of future mobility.<\/p>\n\n\n\n

The question now is how to best capitalize on that momentum. Perhaps now is the time to look at our \u201cchecklist\u201d and take inventory as an industry. Perhaps now is a good time to ask if we have all the disciplines and skillsets necessary to usher in the safer roads we all envision.<\/p>\n\n\n\n

Vehicle Perception vs. Vehicle Cognition<\/h2>\n\n\n\n

Dr. L\u00f3pez-Gonz\u00e1lez and her research needs to make that checklist. Her education, background, and professional experience allow her to view self-driving technology through different lenses. Her vantage point is unique because it identifies gaps that are necessary to close if we want robust and safe automated driving systems. Dr. L\u00f3pez-Gonz\u00e1lez is standing on a different hill in so many words, and as a result, she can view the landscape below differently.<\/p>\n\n\n\n

\u201cWe\u2019ve been systematically researching since the birth of cognitive science in the 1950s,\u201d she said. \u201cI think we need to take all of that research and put it together with the autonomous vehicle world and come up with a map for the future.\u201d<\/p>\n\n\n\n

The industry has worked diligently thus far to incorporate multiple disciplines of engineering and computer science. Now we are adding one that takes into consideration the depth of the human psyche. After all, we will eventually be asking a machine to drive, which has been a remarkably human behavior and activity for the last 120 years.<\/p>\n\n\n\n

\u201cWe shouldn\u2019t be talking about vehicle perception exactly, but rather vehicle cognition,\u201d Dr. L\u00f3pez-Gonz\u00e1lez said. \u201cWe have arrived at an amazing point in AI history, where we can and should close the gap between engineering, policymaking, and cognitive science.\u201d<\/p>\n\n\n\n

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