BROADCASTS.com

\nDoing amazing things for autonomous vehicles\u2026
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\n\n\nIn a trans-Atlantic lunch \u2013 with one guest in California and the other\xa0 in the UK \u2013 Leon Daniels meets with dRISK.\xa0
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\n\n\nChatting with CEO Chess Stetson in California and Business Development/Programme Manager Rav Babbra in the UK, they talk about their work with the government-owned Centre for Connected and Autonomous Vehicles (C-CAV).
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\n\n\nWe hear how they have been tasked by the UK government, through the C-CAVS to build the \u2018ultimate driving test\u2019 \u2013 not for human drivers, but to test self-driving cars.
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\n\n\nTheir test will determine that autonomous vehicles (AVs) are not simply \u2018as safe\u2019 as those driven by humans, but much safer than human drivers.
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\n\n\nWe learn that the test is being used with current AV technologies, to establish how we can get to a \u2018vision zero\u2019 (for accidents) in the UK.
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\n\n\nLeon asks why it is acceptable that 1,500 people a year in the UK are killed by human drivers, yet critics say that AVs must have zero accidents?
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\n\n\nHe discusses why people are not as outranged by existing UK road deaths as they should be, given that 1,500 deaths a year wouldn\u2019t be acceptable in industry or commerce, for example.
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\n\n\nChess opines that the UK\u2019s \u2018zero vision\u2019 towards accidents is a \u201cWorld-leading vision and a much more holistic approach to safety than many other places.\u201d
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\n\n\nHe explains how the driving test for AVs will be used by the DVLA/DVSA when an AV is to be certified for use in the UK.
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\n\n\nLike the UK driving test for humans, the AV version will present a range of scenarios to test the AV.
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\n\n\nWe learn how, using Transport for London (TfL)\u2019s 1,000 traffic CCTV cameras, dRISK has been capturing \u2018edge cases\u2019 - high-risk incidents - and re-creating them in the simulation environment to see what the AV will do.\xa0
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\n\n\nAnd, he poses the oft-asked questions: Will an AV stop for a child running out from behind an ice-cream van, or will it kill it? Other questions discussed include telling the difference between a real human and a dummy.
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\n\n\nChess explains why an AV will be able to recognise that a child dressed in a costume as a green traffic light, is recognised as a child crossing the road, not a green traffic light, even though it\u2019s a situation the AV has never come across before.
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\n\n\n\u201cAVs predict what\u2019s going to happen, not what has happened \u2013 and they can do that now already \u2013 for example, how to deal with the guy in the chicken suit at a level crossing,\u201d he says.
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\n\n\nThe wide-ranging conversation turns to the \u2018naked highways\u2019\xa0 - ones without physical traffic signs and traffic lights \u2013 as the AV \u2018talks\u2019 with the infrastructure and receives instructions.
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\n\n\nThe thorny subject of cyclists and their interaction with AVs is mulled over. Says Chess \u201cCyclists and human drivers never get on; AVs will be able to negotiate their way around them.\u201d
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\n\n\nThen they look at how automation will develop. Will it be a progressive change, or an overnight switch from manually-driven cars to AVs? This leads onto to the increasing automation of existing new vehicles, with systems such as lane keeping and emergency braking already mandatory.
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\n\n\nThe move to full automation in commercial vehciles is examined, and the reasons for hub-to-hub trunking with trucks being the most likely first-adopters.
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\n\n\nThe wider applications for automation are explored, with its use to de-risk the entire transport network.\xa0
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\n\n\nWe discover that already dRISK\u2019s software is used to re-route human driven vehicles to reduce risk. What would be the positive effect on fleet managers if by rerouting, they could reduce their accident claims by 10% in a year? How artificial intelligence (AI) uses data to plan routes that are safest at certain times of day, is explained.
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\n\n\nRav discusses how the integration of AI into transport is no pipe dream, and talks about how dRISK re-purposed its \u2018object detection\u2019 software for Covid, to take feeds from TfL\u2019s roadside CCTV cameras.
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\n\n\nIn this new guise, AI counted people and vehicles, to see the effects of lockdown and monitor social distancing. The results are fed back to councils which can establish if the measures it put in place, for example barriers for pavement widening or space for tables and cafes, are working or not. It can also identify hotspots, for example at pedestrian crossings, where reducing the wait time reduces pedestrian congestion.
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\n\n\nThe conversation concludes with Rav talking about two surveys that are currently open about fleet managers\u2019 opinions on the risks of vehicle routing, and the public\u2019s opinion on AVs.
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\n\nThe Risk Survey - https://www.research.net/r/driskedgecasesurvey\n\n
\n\nThe Public Opinion About AVs Survey\xa0 https://www.dgcities.com/drisk\n\n
\n\nD-RISK project website - https://drisk-project.org/\n\n
\n\n\ndRISK.ai company website -\xa0 https://drisk.ai/\n