St Germain ne Laye, October 8th 2024.
Complexity Reduction Technology, Gain of Time and Money
SafetyNex by Nexyad is a technology that reduces with 100 factor (at least) complexity of development, test and validation for Highly Automated vehicle or HAV.
We do not use Petaoctets of recorded data for treatment in computers farms large as malls. Nexyad worked on a new paradigm based on experience of prudent professional drivers, experts on road safety, and info from insurers, building a metric of prudent driving. Ordinary PC runs our technology using 5% of CPU.
SafetyNex doesn’t identify scenarios, but works on separated elements or events that make up scenarios. We associate a PRUDENCE FUNCTION to each detected element/event in parallel. Prudence functions are dynamic as elements/events are. We fusion them in real time with knowlegde-based, fuzzy logic and possibility theory AI. Doing so, SafetyNex replicates the way humans manage prudence/risk.
Use-Cases Simulation Video of Safetynex
The road, shown in video below, really exists in France near Nexyad office. AI SafetyNex is interfaced with RTMaps of Intempora dSPACE Company in simulation sensors tool AURELION by dSPACE. We just changed trees and houses, but alignment of the road is the same than real world. The legal speed limit is 80 km/h or 50 mph all the way.
Nexyad SafetyNex controls longitudinal and lateral of vehicle. HMI of autonomous vehicle on video shows legal speed sign, current speed on the left, square of prudence (green, yellow or red) with next speed to apply at tapering given distance, and the reason by road sign. Just below, the prudence target accepted: here we have set the threshold of driving prudence at 50% (range from 0 to 100). This corresponds to an occasional driver, not very experienced.
In the following video (eagle & cockpit views), in two use-cases, elements/events are:
a) use-case Winding Curves (prudence function)
b) use-case Curve (prudence function 1) with No Visibility (prudence function 2)
In the second use case (curve with no visibility) two prudence functions are merged*.
So AI SafetyNex manages autonomous driving, reading and analysing a map thru eHorizon and detects winding curves ahead in use-case a, deciding prudent speed at n meters.
Then use-case b, curve (prudence function 1) with no visibility (prudence function 2) is detected both on map (Here Technologies) and by Aurelion sensors (camera). SafetyNex reduces speed anticipating possible object hidden ahead. In this example there a very slow truck on the road. Once truck detected, SafetyNex turns red and decides to brake. Notice that collision was avoided because of the previous slowing down of prudence functions 1 and 2. With the legal speed of 80 km/h or 50 mph, car would have ended up in the truck or in the scenery.
Look at this simple seemingly use-case and think how it can be imagined and recorded in this particular context (this type of curve there) by classical method of scenarios…
*if you want to challenge SafetyNex, and see several prudence functions merged to make a complex situation in urban area for example, contact us.
See more: https://nexyad.net/Automotive-Transportation/prudence-based-automated-driving/
See also: https://wp.me/p4a1CF-3ay and https://wp.me/p4a1CF-39k
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