BRN Discussion Ongoing
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wilzy123
Founding Member
Jumpchooks
Regular
Some examples that’s drivers may encounter in varying situations, there is a Moral issue
Driver with his family in car on tour
1 60 kph drivers sees child on bike come out suddenly ,,,,,, [swerve to miss]
Or, Plastic bag example. Keep driving and ignore ,,,,,, [drive on]
2 100 kph , wet road , driver sees a Kangaroo/Deer jump out from the verge and most advise says they are better to brake and stay driving straight, hit the Roo/Deer and Right-toff the car. All occupants survive. Logic, being that to swerve at that speed could roll car kill the occupants ,,,,,, [ brake hard hit target and survive]
Or, 100 kph drivers sees a child on bike come out suddenly,,,,,,,,,,,,,,[Moral dilemma?]
Just two examples give the complexities of Autonomous Vehicle control decisions.
How does Intelligence fit in to these examples?
When to Brake? ,,,,,,,, When to Swerve?
The human psyche has a high degree of complexity
Jumpchooks
Regular
I was taught to set the Ignition Timing on my vehicles with a cigarette paper in the points. I did it for years until I realized that there was a device called a Timing Light. Still prefer the paper, it gives a very slight advantage (advance)Thanks once again.
I had a mate who would tune the twin su’s on my sports car with a piece of hose stuck in his ear and the other end held in front of each air intake and he would move the hose back and forth until he had them sounding exactly the same.
I wonder if Robot Ken could do this.
FF
Radar transponder with Akida SNN at roofline detects child 0.3 sec before eyesight and reacts 0.3 sec before human driver could.
0.6 sec at 100 kph ~ 16.6 m.
Even cutting that in half still gives an extra 8 m - ADAS emergency program calculates angle of turn to miss child.
Fact Finder
Top 20
The thing about morale dilemmas is there is no right answer the clue is in the question and cheating is impossible.
My experience tells me that best not to drive straight into animals on four legs such as deers, moose, cows, horses, zebra, wilder beast, giraffe etc; because they roll onto the bonnet and through the windscreen and probably kill at least the driver and front seat passenger.
At a practical level do not dismiss this advice as being irrelevant because you live in Sydney as I had a client who survived seriously impaired when on Anzac Parade coming home late at night a horse that had escaped from Centennial Park riding school came through his windscreen.
I think an autonomous vehicle with radar and Lidar would hopefully reduce the surprise factor by very early recognition of terrified horses etc;
FF
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Jumpchooks
Regular
Contrary to the advice I was taught in the 3 courses I had in order to pass the standards to achieve Accreditation to drive in the BHP Pilbarra Mines
AusEire
Founding Member. It's ok to say No to Dot Joining
Hey all
I kept this out of the main threads as I didn't want non members of the forum reading and taking screenshots etc.
Please have a look and give me your thoughts
Good idea, bad idea, what questions etc
Akida Ballista
https://thestockexchange.com.au/threads/brainchip-agm.24329/
I kept this out of the main threads as I didn't want non members of the forum reading and taking screenshots etc.
Please have a look and give me your thoughts
Good idea, bad idea, what questions etc Akida Ballista
https://thestockexchange.com.au/threads/brainchip-agm.24329/
McHale
Regular
That sounds a lot better than bread crumbs.
Fact Finder
Top 20
Did your vehicles have bullbars or were they higher four wheel drive type vehicles?
I am speaking about vehicles like the ordinary passenger sedan.
In the case I mentioned the insurer pleaded contributory negligence and a great deal of expert evidence from different engineers with a range of experience in the area of accident reconstruction reported and they all agreed that the physics supported the risk of an animal in this case a horse rolling onto the bonnet and through the windscreen.
The issue was whether my client was paying proper attention and if he could have avoided the collision.
FF.
TechGirl
Founding Member
Ford smart traffic lights
www.iotworldtoday.com
Ford
Ford is testing connected tech for traffic lights that could save lives.
The company’s European arm has been working on trials of traffic light systems that automatically go green when they’re aware of ambulances, fire engines and police vehicles approaching.
It’s hoped the tech can eliminate potentially fatal delays at junctions as first responders race to emergencies – and also reduce the risk of accidents on the occasions they have to drive through red lights.
Ultimately, the tech could provide the basis for a system that improves traffic flow for all road users.
The tests were conducted on a road in Aachen, Germany, with eight sets of traffic lights, including two stretches with three consecutive traffic lights just outside the city.
A Kuga plug-in hybrid equipped with C-V2X (Cellular Vehicle to Everything) tech was used in two different test scenarios – as an ambulance and an everyday passenger vehicle. The Kuga was fitted with on-board units (for communicating with the infrastructure) and rapid control prototyping hardware (for running the prototype software in the vehicle).
In its role as a first responder, the Kuga signaled to the traffic lights to turn green on its approach. Once it had passed through the junction, the traffic lights returned to standard operation.
For its test of normal, daily driving situations, the SUV was informed by the lights when they would turn from red to green and from green to red. The Kuga then used Adaptive Cruise Control (ACC) to adapt its speed to try to ensure it encountered a green light.
When the traffic light was red, the Kuga’s speed was reduced – for example from 50 kph (31 mph) to 30 kph (16 mph) – well in advance of the junction to increase the likelihood of arrival at the moment the light turned green.
When the timing pattern dictated the Kuga would arrive at the traffic light when it was red, ACC slowed the car down which meant idling time was lessened and congestion reduced.
Among Ford’s partners on the project, which ran from January 2020 to March this year, were the RWTH University Aachen, Vodafone, Straßen.NRW (the road authority for North Rhine Westphalia) and the City of Aachen.
“Exchanging data between cars, emergency vehicles and traffic lights in real time using the latest mobile phone technology makes road traffic safer and more efficient,” said Michael Reinartz, director, Consumer Services and Innovation, Vodafone Germany. “Intelligent traffic light control helps save lives when every second counts and also reduces unnecessary waiting times and cuts CO2 emissions.”
The potential for smarter traffic lights is also being investigated by Tel-Aviv-based NoTrafficwhich has developed an AI-powered traffic signal platform that operates autonomously to increase safety and improve traffic efficiency
Ford Testing Smart Traffic Lights for Emergency Vehicles
The technology could eliminate response delays, reduce risk
SMART ENVIRONMENTS
Ford
Ford Testing Smart Traffic Lights for Emergency Vehicles
The technology could eliminate response delays and reduce accident risk- Written by Graham Hope
- 30th March 2022
Ford is testing connected tech for traffic lights that could save lives.
The company’s European arm has been working on trials of traffic light systems that automatically go green when they’re aware of ambulances, fire engines and police vehicles approaching.
It’s hoped the tech can eliminate potentially fatal delays at junctions as first responders race to emergencies – and also reduce the risk of accidents on the occasions they have to drive through red lights.
Ultimately, the tech could provide the basis for a system that improves traffic flow for all road users.
The tests were conducted on a road in Aachen, Germany, with eight sets of traffic lights, including two stretches with three consecutive traffic lights just outside the city.
A Kuga plug-in hybrid equipped with C-V2X (Cellular Vehicle to Everything) tech was used in two different test scenarios – as an ambulance and an everyday passenger vehicle. The Kuga was fitted with on-board units (for communicating with the infrastructure) and rapid control prototyping hardware (for running the prototype software in the vehicle).
In its role as a first responder, the Kuga signaled to the traffic lights to turn green on its approach. Once it had passed through the junction, the traffic lights returned to standard operation.
For its test of normal, daily driving situations, the SUV was informed by the lights when they would turn from red to green and from green to red. The Kuga then used Adaptive Cruise Control (ACC) to adapt its speed to try to ensure it encountered a green light.
When the traffic light was red, the Kuga’s speed was reduced – for example from 50 kph (31 mph) to 30 kph (16 mph) – well in advance of the junction to increase the likelihood of arrival at the moment the light turned green.
When the timing pattern dictated the Kuga would arrive at the traffic light when it was red, ACC slowed the car down which meant idling time was lessened and congestion reduced.
Among Ford’s partners on the project, which ran from January 2020 to March this year, were the RWTH University Aachen, Vodafone, Straßen.NRW (the road authority for North Rhine Westphalia) and the City of Aachen.
“Exchanging data between cars, emergency vehicles and traffic lights in real time using the latest mobile phone technology makes road traffic safer and more efficient,” said Michael Reinartz, director, Consumer Services and Innovation, Vodafone Germany. “Intelligent traffic light control helps save lives when every second counts and also reduces unnecessary waiting times and cuts CO2 emissions.”
The potential for smarter traffic lights is also being investigated by Tel-Aviv-based NoTrafficwhich has developed an AI-powered traffic signal platform that operates autonomously to increase safety and improve traffic efficiency
Slymeat
Move on, nothing to see.
Not trying to replace the brain but rather trying to emulate the better parts of it and draw upon its efficiencies and adaptability to change. This will somewhat remove the complete reliance on a human programmer who will never be able to consider all situations before-hand, when coding it. Hence my comment on a seed program, a minimal input to define a function only and then the neuromorphic processor can learn from experiences on-the-fly and handle unknowns as presented.
Slymeat
Move on, nothing to see.
A team from Sydney University did a similar trial about 2-3 decades ago. They implemented the smarts in the traffic light system to display a speed to travel at in order to reach the next light in a green state. This was a fuel saving initiative and it worked very well. The government did not support it at the time as they only saw the loss of revenue from fuel taxes. What a pity!Ford smart traffic lights
Ford Testing Smart Traffic Lights for Emergency Vehicles
The technology could eliminate response delays, reduce risk
SMART ENVIRONMENTS
Ford
Ford Testing Smart Traffic Lights for Emergency Vehicles
The technology could eliminate response delays and reduce accident risk
- Written by Graham Hope
- 30th March 2022
Ford is testing connected tech for traffic lights that could save lives.
The company’s European arm has been working on trials of traffic light systems that automatically go green when they’re aware of ambulances, fire engines and police vehicles approaching.
It’s hoped the tech can eliminate potentially fatal delays at junctions as first responders race to emergencies – and also reduce the risk of accidents on the occasions they have to drive through red lights.
Ultimately, the tech could provide the basis for a system that improves traffic flow for all road users.
The tests were conducted on a road in Aachen, Germany, with eight sets of traffic lights, including two stretches with three consecutive traffic lights just outside the city.
A Kuga plug-in hybrid equipped with C-V2X (Cellular Vehicle to Everything) tech was used in two different test scenarios – as an ambulance and an everyday passenger vehicle. The Kuga was fitted with on-board units (for communicating with the infrastructure) and rapid control prototyping hardware (for running the prototype software in the vehicle).
In its role as a first responder, the Kuga signaled to the traffic lights to turn green on its approach. Once it had passed through the junction, the traffic lights returned to standard operation.
For its test of normal, daily driving situations, the SUV was informed by the lights when they would turn from red to green and from green to red. The Kuga then used Adaptive Cruise Control (ACC) to adapt its speed to try to ensure it encountered a green light.
When the traffic light was red, the Kuga’s speed was reduced – for example from 50 kph (31 mph) to 30 kph (16 mph) – well in advance of the junction to increase the likelihood of arrival at the moment the light turned green.
When the timing pattern dictated the Kuga would arrive at the traffic light when it was red, ACC slowed the car down which meant idling time was lessened and congestion reduced.
Among Ford’s partners on the project, which ran from January 2020 to March this year, were the RWTH University Aachen, Vodafone, Straßen.NRW (the road authority for North Rhine Westphalia) and the City of Aachen.
“Exchanging data between cars, emergency vehicles and traffic lights in real time using the latest mobile phone technology makes road traffic safer and more efficient,” said Michael Reinartz, director, Consumer Services and Innovation, Vodafone Germany. “Intelligent traffic light control helps save lives when every second counts and also reduces unnecessary waiting times and cuts CO2 emissions.”
The potential for smarter traffic lights is also being investigated by Tel-Aviv-based NoTrafficwhich has developed an AI-powered traffic signal platform that operates autonomously to increase safety and improve traffic efficiency
Slymeat
Move on, nothing to see.
These type of dilemmas are the reason I had thought I would never see fully autonomous vehicles on public roads (at least not autonomous vehicles controlled by a Von Neumann based computer), yet they exist.
The situations mentioned by @Jumpchooks are but a couple of situations that CAN be thought of and programmed before-hand. That is the trouble with a Von Neumann based system. It needs a set of instructions and set of data that is coded up BEFORE-HAND. This only works with deterministic problems - those for which everything is known, at least for the solution space that is desired.
The trouble I see with a fully autonomous vehicle is that the problem is non-deterministic. I.e. it contains things that are unknown and even things that can never be known before hand. Even the sheer number of knowns is immense.
And as you say @Jumpchooks, the human psyche has a way of dealing with unknowns on-the-fly—intuition, instinct, luck, guess work and pre-emotive thinking are some of the ways of handling unknowns. I suppose this is why neuromorphic processors where first conceived; emulating brain neurons and synapses in a hope to emulate the way the brain forms new pathways to handle new situations, and the more those pathways are exercised the more permanent they become. Hence learning and adaptability to change—a mechanism to deal with unknowns. Isn’t it even more amazing that Brainchip have been able to actually produce this in silicon!
So for the non-deterministic problem of a fully autonomous vehicle we are left with a “good enough” solution. And if that “good enough” solution is better than the best driver on the road, that may even be the “best solution” or at least an improvement and a benefit to humanity. I’m actually ok with that!
How do we determine the “better than” in the above. Basically this is being determined by accident avoidance and responsiveness. But once again, this is ONLY for known situations.
Statistics are gathered that show less accidents, so that is deemed positive.
But statistics also prove more serious accidents as autonomous vehicles tend to plough into perceived non-threatening obstacles at full speed. Crash investigations have shown that fatal autonomous vehicle accidents tend to not have had any attempt to apply the brakes. Turning what could have been a less serious accident into a fatal one.
Remember the Tesla that slammed into a table-top truck turning in front of it on the freeway. Due to heading toward the sun that was low on the horizon, the car was somewhat blinded and did not see the truck. The Tesla hence carried on at speed, resulting in the death of its occupant. An astute human driver may have slowed down as the sunlight conditions made it difficult to fully appreciate what lay ahead on the road. A human driver most likely would have thought to shade the sun. The Tesla had not been programmed to make such a judgement call.
There’s also the dilemma of do least harm and at what cost. When are the occupants of the vehicle deemed less worthy of saving than a group of pedestrians, for instance? Is it based solely on numbers? Or do the autonomous vehicle designers program to protect the vehicle occupants at all costs? That probably is how a human in command of a vehicle would think!
A human driver can say I didn‘t have time to think. But a computer program will most likely always have ample time to run through a large number of potential outcomes and pick one that best meats its programmed parameters. And whoever designs those parameters should be accountable for the outcome.
This adds strength to the recent Mercedes announcement that the company will take responsibility for accidents. I fail to see how this will actually apply in the case of a fatality, and especially internationally. Will some company exec or developer wear man slaughter, or even murder, charges if proven that the design/coding had malicious intent either deliberately or even by omission?
I suppose only time will tell.
It will all come down to the value of a life metric, multiplied by the expected number of lives lost compared to the number of lives saved (assuming that is possible to determine). It will all come down to money!
Personally I would never be a willing passenger in a driverless vehicle. I like the act of driving and of being in control. Getting from point a to point b is not the sole purpose of any trip I go on. I derive a lot of pleasure out of the act of driving.
I am 100% supportive of driver assist technology as it can enable the driver to enjoy more of the driving experience by taking care of some of the more mundane tasks (e.g. sticking to the speed limit) and it does improve safety.
Slymeat
Move on, nothing to see.
I never new anything about BrainChip Studio or BrainChip Accelerator before. Let alone full-blown surveillance solutions. I wasn’t even aware they were into developing systems.
The article references an award won 5 years ago (Milpol 2017). Does anyone else have any insight into these products. Do they still exist and why would this article be written TODAY!
This stuff is not on the BrainChip web site.
I thought this article was discussing some other like-named company, but it isn’t, it is definitely talking about our BrainChip. The article seems to emanate from an office in France.
Go Figure hey!
https://www.securityworldmarket.com...IuXFX9yVfm_D0VjZobO00yr7UHScIM7KYqm1boePKVmKM
The following is from the above article published 31 March 2022
BrainChip Studio
BrainChip's civil surveillance solutions provide law enforcement, homeland security, and intelligence agencies with the ability to rapidly identify objects or faces in large amounts of archived or live streaming video. The combination of BrainChip Studio and BrainChip Accelerator can process 16 channels of video simultaneously, with a total throughput of over 600 images per second. BrainChip Studio was recently awarded new product of the year for video analytics by Security Today and BrainChip Accelerator received the Innovation Award during the Milipol 2017 conference.
BrainChip Studio runs on standard x86-based desktop and server platforms with most common video file formats. It is currently available to select law enforcement and intelligence agencies.
BrainChip Accelerator
BrainChip Accelerator is an 8-lane, PCI-Express add-in card that increases the speed and accuracy of the object recognition function of BrainChip Studio software by up to six times. It does this by accelerating video scaling, spike generation, and spiking neuron model comparisons. In combination with a CPU that has 16 virtual cores, BrainChip Accelerator can process 16 channels of video simultaneously, with an effective throughput of over 600 frames per second.
The low-power characteristics of BrainChip’s spiking neural technology results in a power-sipping 15 watts total consumption. This results in a lower total cost of ownership compared to using additional servers.
The article references an award won 5 years ago (Milpol 2017). Does anyone else have any insight into these products. Do they still exist and why would this article be written TODAY!
This stuff is not on the BrainChip web site.
I thought this article was discussing some other like-named company, but it isn’t, it is definitely talking about our BrainChip. The article seems to emanate from an office in France.
Go Figure hey!
https://www.securityworldmarket.com...IuXFX9yVfm_D0VjZobO00yr7UHScIM7KYqm1boePKVmKM
The following is from the above article published 31 March 2022
BrainChip Studio
BrainChip's civil surveillance solutions provide law enforcement, homeland security, and intelligence agencies with the ability to rapidly identify objects or faces in large amounts of archived or live streaming video. The combination of BrainChip Studio and BrainChip Accelerator can process 16 channels of video simultaneously, with a total throughput of over 600 images per second. BrainChip Studio was recently awarded new product of the year for video analytics by Security Today and BrainChip Accelerator received the Innovation Award during the Milipol 2017 conference.
BrainChip Studio runs on standard x86-based desktop and server platforms with most common video file formats. It is currently available to select law enforcement and intelligence agencies.
BrainChip Accelerator
BrainChip Accelerator is an 8-lane, PCI-Express add-in card that increases the speed and accuracy of the object recognition function of BrainChip Studio software by up to six times. It does this by accelerating video scaling, spike generation, and spiking neuron model comparisons. In combination with a CPU that has 16 virtual cores, BrainChip Accelerator can process 16 channels of video simultaneously, with an effective throughput of over 600 frames per second.
The low-power characteristics of BrainChip’s spiking neural technology results in a power-sipping 15 watts total consumption. This results in a lower total cost of ownership compared to using additional servers.
Techinvestor17
Regular
Where are you seeing the publication date?
uiux
Regular
Frank Zappa
Regular
Alcohol
, drugs , onset dementia, txting , LCD screens set into front dash board , pedestrians with short skirts , no IQ set for anyone to apply for a licence , 4.4 million people in Australia diagnosed with mental health issues which has increased from next to none 50 years ago, I’m still out there driving , that would probably be the main concern .
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