Tag: Google

Sudenkuoppia: Mitä Google-haku kertoo GMO:n turvallisuudesta?

Olen viime kuukausiin asti olettanut, että älykäs ja pätevä ihminen pystyy selvittämään asioita ihan vain googlaamalla niistä tietoa. Vaikka netti on täynnä disinformaatiota, terävä ihminen tunnistaa sen.

Sitten erehdyin kokeilemaan.

Olin toukokuussa mukana tekemässä aloitetta, joka halusi muutosta Vihreiden linjaan geenimanipulaatiosta.  Aloite ei mennyt sellaisenaan läpi, mutta aiheesta tehdään kuitenkin selvitys, mikä on positiivinen askel.

Aloitteen pääväite oli, että nykyään on tieteellinen konsensus siitä, että geenimanipulaatio ei tekniikkana ole sen turvattomampi kuin muutkaan jalostusmenetelmät.  Väite herätti vilkasta keskustelua, osa äärimmäisen hyvää ja hyödyllistä. Aloite teki sen mitä pitikin, eli herätti monet ihmiset selvittämään kysymystä itselleen.

Mutta miten tällaista asiaa sitten selvittää, jos aikaa ei ole rajatomasti? Itse teen tällaisissa tapauksissa Google-hakuja. Yksinkertaisuuden vuoksi tein tätä kirjoitusta vain yhden haun, hakusanoilla “GMO consensus”,  ja pyrin luokittelemaan ensimmäisen 40 osumaa. Tulokset olivat yllättäviä.

Continue reading Sudenkuoppia: Mitä Google-haku kertoo GMO:n turvallisuudesta?

Executions (per 100 000 people)

I was inspired by a Google+ conversation about this figure. So I took numbers of executions from here and population from here (28 January 2013). Execution numbers are from 2011 and population, I think from 2008 to 2011. Malaysia and Syria were not included as no number was given in the source for the number of executions. For China I rounded the number to 1000 even though the source gives an estimate from about 1000 to 4000. The original spreadsheet can be found here

Executions per 100kFigure 1. Number of executions per 100 000 people in 2011

 

log executions per 100 kFigure 2. Log(number of executions per 100 000 people)*(-1). Same as figure 1 but emphasizes differently.

Executions histogram

Figure 3. Histogram of execution densities.

Table 1. Data the images are based on.

Execution data

Edit: Added Figure 3.

Future with driverless cars 1: Rental vs. taxi

 

This is the first part of a series on changes that driverless cars may bring. I expose some of the ideas I have, mostly quite practical things. There may also be more profound changes on how people see the world but my looking glass is out of focus with such matters.

We moved project troglodyte to it’s own website, so the more patent centric recap of the Google driverless car patents can be found from there.

Below I assume that the problem has been solved completely. Driverless cars can access any part of the road network, function even when there are people darting around and can handle any weather including lots of snow and very slippery conditions. Accident levels are same or lower than currently and people are not scared to use autonomous cars.

See also: Rental vs. taxi, Mass transportation, Pirvate cars, Cargo, Parking and driving empty, Zoning Traffic volume and Externalities

The distinction between renting a car and taking a taxi will disappear. When a small car is needed it can be called for from any comms unit. It is possible that this will create a pressure to move away from the personal automobile affection as getting a rental car to any location is as easy as asking for a taxi as the rental can come to the renter and not vice versa. But this is not necessarily the case. There will still be a delay in getting the rental. This might not make a big difference for longer journeys taking several hours, but for shorter intra city traveling the difference might be too large.

When the road network extends very close to one or both ends of the trip journey times will be shorter than now for the rental (or a private) car as it can can pull up at the door and find a parking spot by itself after the passengers have left. A taxi is usually rented only for one leg of the journey at a time, but this is largely because of the cost of the driver. If a taxi was much cheaper many might want to get rid of the waiting in line by reserving the car for themselves in the same way a rental car is often rented for a longer period.

While a driverless taxi will be cheaper it  will of course lead to a massive reduction in the need for taxi drivers. There will likely still be some cases where a human might be needed, to help elderly or disabled passengers to get to the car etc. In these cases it might be economical to share one driver between several cars, for example if the customer is visiting a place where help is available at the other end the driver may change to another car on the way to assist someone else. The relative cost of a car with driver will be higher than now which will lead to pressure to reduce their use especially in cases of subsidised trips.

For a car of comparable size a driverless taxi will have a larger passenger capacity by at least one, possibly more as the seating arrangement can be made more freely. Because there is no driver to oversee the passengers, interior of the vehicle may need to be more durable, but on the other hand use of mass production models straight out of the factory is cheaper than using modified vehicles.

In some places offering taxi service is subject to licence. The rationale for this includes driver proficiency, health, reputation etc. It is difficult to see how such licences would be needed in the case of driverless taxis. This is likely to lead to more widespread secondary use of personal cars as taxis. While the owner is working or sleeping the car can drive around the town transporting passengers as needed. This will give a further advantage to those who can arrange their lives so that their traveling is off peak.

Acknowledgment:  Thanks to Laston Kirkland for thoughtful evaluation of these ideas.

Troglodyte Driverless vehicles 5

 

SYSTEM AND METHOD FOR PREDICTING BEHAVIORS OF DETECTED OBJECTS

“Majority of the description text could be condensed to: autonomous vehicles should mimic the behavior of human drivers.”

The purpose of Project Troglodyte is to hunt for bad patents and to show what went wrong. For more information, please see the web page.

This patent is the fifth in a series of Google autonomous vehicle patents/applications analysed to get an understanding of the level of their inventions and the state of the autonomous car project.

 

Figure 1.

 

TIER 1: SUMMARY

It appears that the main purpose of the application is to expose a lot of prior art in one document, to make sure that it is easily found and public. This conclusion is made as there are about 12 000 words in the description but the claims only touch a very small part of it and much of the description text is obviously obvious to anyone skilled in the art, or misquoting from the application: “…understood by those of ordinary skill…“.

The actual idea that protection is sought for is changing how the vehicle is controlled based on detecting an object, classifying the object and based on the classification predicting the behavior of the object. And as Google is involved, creating a massive cloud based database of said behavioral data and sharing it around.

Majority of the description text could be condensed to: autonomous vehicles should mimic the behavior of human drivers. The description explains that processing of the object related information can be done at a location external to the car, this is also mentioned to be possible for the processing related to vehicle control decisions. This might open an interpretation that any controlling of traffic based on information originating in behavior prediction of single vehicles would fall under the protection of this patent. It would mean that any system arbitrating route decisions between vehicles to lessen traffic jams might need to license this.

Being able to predict behavior of nearby objects based on common experience is a valuable feature and will make traffic flow faster and safer. It isn’t mandatory for every autonomous vehicle though and thus wouldn’t likely block competitors from entering the field.

 

TIER 2: AVOIDING LICENSING

It seems that the possibility of using predictions of object behavior of nearby objects observed by other vehicles (or systems) is not mentioned. This would be useful in case large objects create shadows preventing direct observation. Using direct or network based vehicle to vehicle communication might be bandwidth limited in transferring the whole awareness of another vehicle. It would also be wasteful in use of processor resources as the same data would have to be analysed several times, so it would be prudent to  transfer only information deemed important for other vehicles.

If the classification scheme is left out it makes it possible to implement simpler threat prediction based on observed speed and direction. It would still be possible to use context dependent database to predict that for example vehicles in the left lane are more likely to transfer to the right lane during a certain time window at a certain time. This would likely be good enough for autonomous vehicles, but it would be less optimal as the classification scheme will lower the number of times the vehicle needs to alter it course to accommodate other vehicles. Vehicle without the classification ability would likely appear more selfish but if all vehicles are eventually  automated this would have less of an impact as it would now when all the drivers are humans.

 

TIER 3: TECHNICAL ANALYSIS

As stated above, major part of the description just portrays how humans approach driving. Context sensitive behavior prediction of classified objects is what humans are good at. But sharing the accumulated experience between humans is cumbersome. With this invention autonomous vehicles could share automatically on a massive scale. The invention here is not mind boggling, but they usually aren’t. I didn’t do a proper prior art search so it could already be out there, but generally this type of thing (essentially an optimization of a more general approach) is less likely to pop up in science fiction than most of the other stuff in the description.

The description is mostly useless. If the patent system worked, most of the stuff would have to be cut. If there is need to create prior art to stop trolls, write a white paper and publish it somewhere. For the price of a patent attorney it is probably possible to buy enough space in some regional newspaper to show the whole 12 kwords. On the other hand the description of the invention itself is very shallow in detail. Much more should have been given regarding possible ways to implement it, how to handle false identifications, how to handle different sensing abilities, who is responsible if bad data leads to accidents etc. Of course if the patent office doesn’t require this then it would be foolish for anyone to give it. Writing it down might have given a good patent engineer the chance to claim more and could have made this patent more valuable.

The claims only use a small portion of the text but cover that part fairly well. They are almost understandable, although the last one is complex enough that reading it requires more uninterrupted concentration than is usually available when the kids are around.

Troglodyte: Driverless vehicles 4

 

“The idea is perhaps geared a bit too much around the concept of a “driver” and the thinking that she is actively following what the car does.”

The purpose of Project Troglodyte is to hunt for bad patents and to show what went wrong. For more information, see the  web page.

 

Zone Driving

This analysis is part of a series of Google driverless car related patents and applications. This application can be found here.

When reading the analysis it might be interesting to keep in mind that Google possibly uses this idea in their test cars all the time. It would be interesting to know how much the test drives are affected by it. If driverless car development wasn’t a sideshow for Google this could even have an impact on its market value as it could conceal the technology readiness level.

Figure 1.

TIER 1: SUMMARY

This application describes a way of generating, sharing and using information about areas where the driver might want to take control of an autonomous vehicle. These areas are called zones in the text. The idea is perhaps geared a bit too much around the concept of a “driver” and the thinking that they are actively following what the car does. I for one think the exact opposite is the reason to buy an autonomous vehicle in the first place.

My real problem with this idea is the wordplay; a zone is defined as a place where the autonomous vehicle is not that autonomous or where there is a risk that it can’t cope with the environment. If a company wants to come to market before it can handle every aspect of the traffic environment it need this sort of approach. For example the vehicle avoids certain types of intersections or areas of intense pedestrian traffic where it might not be able to move as the pedestrians would be very close. One might be able to argue that a system driving solely on highways needing the driver to take control when exiting the highway is using this system if it automatically recognizes the upcoming exit and gives a warning. This in turn is pretty much a must, as highways sometimes morph to regular roads. Defining the points where control is needed as zones makes it sound like this would be something completely new.

While I don’t know how novel this idea is (I didn’t do a prior art search) it is certainly a powerful way of categorising this information. After realising what is meant by a zone the rest of the related ideas kind of flow naturally.

I would imagine that this is something the development team stumbled into as they wanted to try the car before the algorithms were able to control it in all circumstances. The difficulty of environments likely varies greatly, so it is prudent to start with the easier ones to get some experience. Come to think of it, it is possible that the first autonomous cars will be limited in their ability to navigate completely independently as they probably will be developed from cars that have some of the required features but not all, for example from cars that will be able to drive in light traffic on divided highways.

One important aspect might also be the reluctance of drivers to leave all control to the computer, this fear would likely be alleviated if there was a possibility to set parameters that trigger a notification about difficult spots. As one of the main reasons to get an autonomous car is to be able to do something else when travelling, this sort of warning/notification feature might be a must for all early models.

I noted in some of the other driverless car analysis that they are transition period ideas, that is also true in this case. The proposed feature would get most use when the roads are not built for autonomous vehicles and people are not used to the new technology. After the transition period it might get very little use as it would be required only in exceptional circumstances.

 

TIER 2: AVOIDING LICENSING

The zone concept could be further developed by adding some parameters such as time of day, day of week, temperature, forecasted low friction, local rush hour etc. Pop-up zones could be created if a school bus is detected or a driver indicates that one is close by, this sort of zone could expire for example in 15 minutes. The computer could automatically generate zones if it needs to use unexpected deceleration or manoeuvre violently to avoid impact.

Further there could be a voting scheme to establish and remove a zone. For example if one driver indicates a zone is needed those approaching immediately behind would get a zone warning, but if none of them takes control of their autonomous vehicle the zone would not be established.

Two obvious methods of bypassing exist, the driver follows the situation closely or the car really is autonomous. Neither is good for the business of selling autonomous cars. One possibility might be to analyze map data constantly to identify spots where the computer might need help. Roadworks are often indicated by signs which can be recognized by cameras. Some places could be indicated by a special sign which might have an RF transmitter to make them detectable beyond visible range and add some determinism. These however do not quite reach the dynamic nature of the zone idea (its best contribution I think) which could prove to be quite difficult to bypass if this application is granted in its present form.

 

TIER 3: TECHNICAL ANALYSIS

The word vehicle is used throughout the text, by definition it includes things such as aircraft and helicopters. Autopilots have been in use in those for some time, devices such as autothrottle seem similar to the description of taking over part of the control from the computer. Aircraft autopilots also disengage if they lose control and naturally give a warning. Almost certainly modern autopilots can be engaged for a part of the planned route and be configured to give a warning before that part ends. For example an autopilot would be used through cruise and a warning would be given when the planned descent point is reached. If the descent point is called a zone, it is at a waypoint and the waypoint information can be found on a map which is downloaded from a server the similarities a quite noticeable.

Without the zone system drivers of early autonomous vehicles may feel the need to continuously monitor the performance of the car. With it they may first set a very strict warning level and include a lot of zones and after they feel more comfortable they can let the car do more and more of the driving by itself. Because the zones are proposed to be in a map, any route can be designed so that the number of zones on the route are as few as practicable. If the driver feels tired she can select a route that is a bit longer but has less zones in it and use the time to rest.

In the description it is noted that it is not sufficient for the vehicle to be close to the zone to trigger action, the vehicle also needs to be affected the by the zone in the future. For example if the vehicle is driving on a lane that is on top of the zone on a bridge, no action is required. This is important for the functioning of the zone concept as false positives could degrade user confidence in the system. To be able to solve this problem one needs understanding of the map side of the equation: when the route is planned and then followed, the computer knows which lane it is likely going to be on when the vehicle is close to the zone. The description of this is rather sketchy and actually making a system that does this requires some knowledge of an art that is not that closely related to the zone concept.

The claims are related to the description. As mentioned above some part of the idea may have novelty issues and this of course reflects on the claims that cover that part of the description.

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