Human experts help surface important nuances that help the system learn faster and interpret more complex scenarios. For example, AI technology might detect a lane departure and trigger a video event clip. We know that lane departure is highly correlated with distracted driving such as texting. However, a human reviewer might notice that this swerve was due to a construction area forcing all traffic to make a sudden lane change. This type of nuanced data is important in helping to refine, learn, anticipate what might happen next and become more sophisticated along the way. Lytx events have been reviewed by humans for over 10 years.

For example, when a vehicle approaches a stop sign, machine-vision technology scans the sign and recognizes it. The system also uses speed data to detect whether the driver came to a complete stop. If the accelerometer detects that the vehicle didn't come to a complete stop the DriveCam system triggers a video clip.


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This unit is comprised of an MDI Compact sign and a WindMaster sign stand (each sold separately). Once the sign is mounted to the stand it becomes one unit, and, if desired, the sign can stay with the stand. To store, the sign quickly collapses down using the single trigger release button and wraps around the upright on the stand. The rapid deployment significantly improves safety and efficiency in the work zone.

Hi all! In KRC2 I would like to implement an emergency Stop during a program or subprogram run by using a signal input. In more detail I would like it to work similarly as an interrupt style routine but simultaneously enable all the functions that the controller's E-stop enables plus to Kill all OUT's signals.

However, if you want to use a "soft" signal rather than the E-Stop itself, you can create your own Interrupt Service Routine, based on an Interrupt of your choosing. Your ISR could be written to set all $OUTs in a given range to False, and also call IR_STOPM as a subroutine.

However, if you want to use a "soft" signal rather than the E-Stop itself, you can create your own Interrupt Service Routine, based on an Interrupt of your choosing. Your ISR could be written to set all $OUTs in a given range to False, and also call IR_STOPM as a subroutine.


That was my initial thought and thats what I did. I created a interrupt with an input that included BRAKE and OUT's Off until I learned that it is forbidden to use an interrupt this. No man is allowed in the robot working area while an interrupt "dummy e-stop" is enabled.

We used Bayesian cognitive modelling to identify the underlying causes of apparent inhibitory deficits in the stop-signal paradigm. The analysis was applied to stop-signal data reported by Badcock et al. (Psychological Medicine 32: 87-297, 2002) and Hughes et al. (Biological Psychology 89: 220-231, 2012), where schizophrenia patients and control participants made rapid choice responses, but on some trials were signalled to stop their ongoing response. Previous research has assumed an inhibitory deficit in schizophrenia, because estimates of the mean time taken to react to the stop signal are longer in patients than controls. We showed that these longer estimates are partly due to failing to react to the stop signal ("trigger failures") and partly due to a slower initiation of inhibition, implicating a failure of attention rather than a deficit in the inhibitory process itself. Correlations between the probability of trigger failures and event-related potentials reported by Hughes et al. are interpreted as supporting the attentional account of inhibitory deficits. Our results, and those of Matzke et al. (2016), who report that controls also display a substantial although lower trigger-failure rate, indicate that attentional factors need to be taken into account when interpreting results from the stop-signal paradigm.

CBD can be used as an off-ramp from the busy, frantic mode we sometimes (often) find ourselves in. It can shift us to a lower gear. It allows us to make a full stop at the stop sign rather than blow right through it and suffer the consequences.

Thanks Andrew. It's working. My first mistake was adding 10u to risetime to stop simualtion. That's not correct. tcross is correct one. Operator @ really helped me. Sorry about font, I will stick to default one.

That's not going to work. I'm assuming you're talking about adjusting an ADE output expression (using clip). For a start, you're not exporting clkdelay or stop_time, and even if you were, the dimensions are completely wrong (clkdelay is a voltage not a time, and hence so is stop_time). You could use the mechanism described in How to use an MDL script within ADE (remembering to set the mdlpsfoutput setting in current versions) to use an expression to read the exported results back into ADE, but in this case it's unnecessary.

If you really need to know what the final x-value is in an ADE output expression, you can use lastVal(VT("/vout")) (use an appropriate signal name that you have in the design). As I said though, with clip() this is unnecessary you can just do: clip(VT("/vout") 13u nil) or something like that.

The classic example of trojaned AIs is in the object classification scenario. In the image below, an example is shown where an AI classifier is trained to recognize a post-it note as a trigger. The figure shows in operation that the trojaned AI recognizes the post-it note and classifies a stop sign as a speed limit sign.

Reinforcement learning agents can also be trojaned. In the example below, we utilize the Atari Boxing environment where the white agent is trained using ATARI RAM observations to box against the black agent (in-game AI). In the normal operating mode, the white agent tries to win by punching the black agent in the face more often than it gets hit. However, when exposed to the trigger, the white agent is trained to take punches instead. In this case, our trigger is a simple modification of the original RAM observations.

Object detection AIs are also vulnerable to backdoor attacks. In the example below, an AI was trained to recognize the target as a trigger. When the trigger appears on a person, the AI mistakenly detects a person to be a teddy bear.

I was searching for quite some time but I was unable to find a simple solution.I have a python script that runs indefinitely and saves some files when a condition is met (enough data gathered). Is there a way to terminate the execution of the script and trigger a function that would save the gathered (but yet unsaved) data?Every time I have to do something (let's say close the computer), I must manually stop (terminate) script (in Pycharm) and I loose a part of the data which is not yet saved.

The first example looks like you do need to set the mutually exclusive start-stop signs, implying that the general setting is ignored...? In fact it doesn't let you see what the general settings are. If the default setting was the same as one of the two start-stop times, would you still need both start-stop times?

The second example has a start-stop time that has the same settings as the general time, and only has one start-stop time, so I don't get what the purpose is? It's like saying "in general, trigger every 30 seconds... but between 20 and 06 trigger every 30 seconds"

The general settings is not a default for the start-stop times outside of those windows. Basically if your two start and stop times don't incorporate all 24 hours of the day then during those times not included the camera will be inactive. I hope this clears things up for you.

Okay, first you are confusing trigger interval with time lapse. 30 second trigger interval means to WAIT 30 seconds between sending a picture and taking another. It doesn't mean take a picture every 30 seconds. With longer trigger intervals (e.g., 5 minutes), the camera will take a picture every 5 minutes, not stay quiet for 5 minutes between the time it finishes sending and the time it takes the next picture. edited to add: as long as there is motion in front of the camera. (Taking a picture every 5 minutes no matter what is time lapse, the other setting you can choose.)

The second example is for a security situation when you are active in the area during the day and don't want forty-'leven photos of you doing stuff but you want the area monitored at night. The camera will go on duty at 8 PM, it will take and send photos with a 30 second quiet time between send and taking the next photo, and it will stop taking photos at 6 AM.

In the first screen shot, the only reason that you can't see the general settings is because they are scrolled out of sight so you can see both start-stop times. That's a screen shot of the (old) iOS app. If you look at the second screen shot, from the (old) Android app, you will see that you can still see the regular settings right above the two start stop times. It's just a matter of what is shown in the screen shots, not that you can't get to them to see them.

DriveCam video is captured by an event recorder mounted on the windscreen of the vehicle. In addition to video camera lenses, the event recorder is packed with sensors that can detect more than 70 driving behaviors, from rapid acceleration to excessive speed. Lytx is also adding valuable new video capture triggers to identify and help extract even more risk from commercial and government fleets.

Rolling stops are common among urban drivers, especially those in a hurry to get to their next service call or delivery, or to complete their route. Rolling stops are also dangerous and illegal, and unfortunately, they're associated with thousands of injury and fatality collisions each year. Lytx has developed and patented new way for fleets to identify when their drivers go through a posted stop sign without coming to a complete stop. This Rolling Stop trigger will initiate video capture for use by fleets in coaching the driver to help eliminate the behavior. ff782bc1db

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