Author: Niko Porjo

Joys: comedy, cycling and spotting argumentation errors in live speech. Physicist and thinker, a little bit of an amateur philosopher. I like to build things but when they work that’s enough, no polishing.

Päivän heitto 9.9.2012: Asuntojen hinnat Turussa

 

Odotetusti etäisyys keskustasta laskee hintoja. Pienillä etäisyyksillä hajonta on kuitenkin melko suurta.

Tavasin aamulla teetä juodessa Soininvaaran blogia ja erityisesti tätä kirjoitusta ja sen keskustelua. Kerrostalokaksioiden hintoja listattaessa Helsinki oli jaettu neljään vyöhykkeeseen joissa neliöhinnat poikkeavat toisistaan merkittävästi. Kuten keskustelussakin mainittiin, intuitiivisesti etäisyyden täytyy vaikuttaa hintaan muuallakin. Intuitio ei kuitenkaan aina pidä paikaansa, joten yritin tarkastella tilannetta vähän tarkemmin katselemalla mitä vanhojen kerrostalokaksioiden pyyntihinnat (koska niitä on helppo löytää) ovat tällä hetkellä Turussa ja ympäristössä.

Annoin Google mapsin laskea ajomatkan ja ajan asunnon osoitteesta Turun keskustaan (torin laidalle). Tässä ei tietysti huomioida ruuhkien vaikutusta aikaan, mutta se lienee jonkinlaisessa suhteessa toteutuviin aikoihin. Aineistoa kertyi 91 kappaletta joista merkittävä enemmistö on Turussa ja vain muutamia naapurikunnissa. Otanta oli lähes satunnainen; lopussa en ottanut enempää Turun keskustan asuntoja mukaan kun niitä jo oli aika monta.

Alla on muutama kuva joista voi kukin tehdä omia päätelmiään. Itsellä silmiin pistää suuri hajonta neliö hinnoissa keskustan lähellä. Suurempi hajonta noin kymmenen kilometrin kohdalla voi johtua Kaarinan ja Raision keskustaajamien sijainnista tuolla etäisyydellä. Ajoaikakäppyrässä suuri hajonta jatkuu pidemmälle.

Kuvassa viisi on nähtävillä myynnissä olleiden kaksioiden pinta-alojen histogrammi. Dataa kerätessä jäi kuva liikuttavasta yksimielisyydestä kaksion oikean koon suhteen. Todellisuus on vähän monipuolisempi.

Niin ja mediaani pyyntihinnaksi sain 1950 €/m2 joka on aika lähellä Soininvaaran blogissaan mainitsemaa.


Kuva 1.


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Kuva 6.

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.

Troglodyte: Driverless vehicles 3

“They call it a landing strip. In my mind this is the same as having a sign over the road telling you where you are.”

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

 

Transitioning a mixed-mode vehicle to autonomous mode

I recently run into this article. I browsed through the patent, here are a few comments. Note: this analysis was originally done before we developed the analysis template so the approach differs a little from the rest.

Figure 1.

 

TIER 1: SUMMARY

This patent seems to describe a way of reading a reference indicator (e.g. a marking in the road) and using this info to both determine the exact location of the car and to retrieve data that the indicator points to. Basically there would be a QR code in the road at some location, which is possibly a place where the vehicle stops. They call it a landing strip. In my mind this is the same as having a sign over the road telling you where you are. What about snow and ice? It is difficult to read the QR code if it is under snow. This may have been overlooked as all the inventors seem to be from California, maybe Mountain View, and according to wikipedia snow isn’t really a big problem there. But to be fair, they do indicate that using RF technologies could be used to implement the same functionality. It can, but getting the same location accuracy would be more challenging.

Is there any harm in this patent being granted? There might be if they manage to push through the idea that a computer reading road signs and taking actions based on that is now a google monopoly. It might be difficult for Google or anyone else to push through such a wide interpretation of this patent but who has the money to challenge them?

While the ideas are somewhat useful they are not that innovative. There can be several reasons for this, one is that the best parts of the application needed to be dropped during the examination (due to prior art) by the patent office but they decided to go through with it anyway. A more cynical view might be that just before the filing date someone decided that the driverless car thing might go forward and we need to patent something stat. To be complete it is worth mentioning that I may just have fallen for the trap that I have seen many times before: things are much more obvious after someone has written them down.

 

TIER 2: AVOIDING LICENSING

As usual the description includes a lot of stuff that is already known or otherwise obvious, for example about a page is used to describe the computer system that might be running the logic needed to use the indicators. I’m not very skilled in the art of autonomous vehicles but my feeling is that the description didn’t really include anything that the public would benefit from. This is mainly because reading a QR code or other indicator is exactly analogous to what one does when reading a sign with location information. Adding the use of an url to retrieve instructions doesn’t really make a difference in the inventiveness department. I’m left wondering what was the original idea that they invented and at what point was it removed from the patent? Also, the title and the description don’t really match. While this is nine kinds of bad when writing a school assignment it might be good for a patent (if you are the inventor) as it is more difficult for the competitors to find the information.

This patent might not be that difficult to bypass. In the short term just record the orientation and location of many road signs and use the vehicle’s approximate location from GPS or sensors to check which sign it is and then retrieve this info from a database.

 

TIER 3: TECHNICAL ANALYSIS

If the QR code (indicator) includes position and orientation (of the indicator) a camera can be used to get a very accurate position, “easily” with in millimeters related to the indicator. This could be useful in a few situations:

  • There is no GPS coverage
  • The GPS location accuracy is not enough to resolve the location ambiguity due to say roads being on top of each other. This can usually be deduced from the path history, but it is good to have some redundancy, if there is reboot or something.
  • On a bridge, tunnel or similar location a Lidar or radar may not have enough information as the environment is completely built or “empty”
  • The environment has been changed beyond recognition due to construction etc. I have understood that the google approach uses prior knowledge of the environment to determine the location by comparing sensor info to database. It might be that if the road has been closed for changes that the environment, not to mention road location has changed drastically. In such a case the QR code could have info on how to cross the changed part of the road until the database has been updated by the passing vehicles.

It looks like these ideas predate the lidar approach but this has been filed on May, 2011 (now is 27 July, 2012) and as long as I know google’s lidar tech using Prius is older than that. So they may have been thinking about one of the bullets above where it would be quite handy say if there is a construction in a tunnel and vehicles need to be told what to do. It is worth noting that inertial sensors can be used for fairly accurate guidance for a short while and even dead reckoning is likely good enough to avoid a couple of cones and a steamroller if it is in a designated area. Doesn’t have much to do with transitioning to autonomous mode though.

After reading the claims I have two things in my mind:

  1. I can recognize the description from the claims, which is nice and not always the case
  2. If they manage to get another patent where they define wetware to be a computer I will need to start paying licensing fees every time I drive a car.

Troglodyte: Driverless vehicles 2

“Effectively they attempt to patent the exact thing every good driver 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.

DIAGNOSIS AND REPAIR FOR AUTONOMOUS VEHICLES


This patent is analyzed as part of a series of Google driverless car patents and applications. It is an emerging technology area which, I feel, will have a significant impact in 7-20 year time frame, perhaps even earlier. Existing Intellectual Property will make a difference on how the field develops.



Figure 1.


TIER 1: SUMMARY

A system where sensor information is used to determine wear or damage to parts of the vehicle, this information is then combined with information from environmental sensors and with map data to alter behaviour of the vehicle. For example: if the brakes are worn the system would use smaller deceleration than when the brakes are new. This is done to extend the life of the brakes, presumably until they can be overhauled. While the claims don’t seem to include it, the description also introduces a possibility for the vehicle to automatically seek a repair facility.

If this application is granted as is, it would likely cover some fundamental aspects of automated vehicles. It would cover a situation where external sensors indicate water on the road and the vehicle is able to sense significant tire wear and then decelerates to avoid hydroplaning. The current application doesn’t even attempt to explain how any of this is done; it is a description of a system that decides between different actions based on sensor and other inputs. Effectively they attempt to patent the exact thing every good driver does.

It should be noted that while the claims give an impression that this is about cars, it can be considered to cover other types of vehicles such as airplanes. In fact in the description  trucks, motorcycles, busses, boats, airplanes, helicopters, lawnmowers, recreational vehicles, amusement park vehicles, trams, golf carts, trains and trolleys are mentioned as examples of vehicles.

Looking at the news, it seems driverless car development is all about sensor fusion. Adequate sensor technologies are available, but putting together a system that makes sense of all the information takes a lot of work. Protecting solutions to problems that are encountered during development is standard practice. If granted this would in a fairly broad manner give Google a handle over an important optimization aspect of driverless vehicles.

TIER 2: AVOIDING LICENSING

Using a FEM model incorporating current sensor information to predict the response of the vehicle to current conditions could be used to change the behaviour without resorting to selecting from a list of possible actions. It is difficult to say if this differs enough from the language of the claims to be outside the scope of this application, but it could be useful in any case.

The obvious bypass route is to not use information about damage or wear to components internal to the vehicle. This however could restrict how aggressively the computer could use the vehicle as it would in some cases need to make a worst case assumption about the state of vehicle systems.

TIER 3: TECHNICAL ANALYSIS

The inventive step seems to be missing so discussion of novelty is a bit academic, but looking at novelty of the different parts can show that their combination is fairly obvious. Using sensors to monitor the internal wear and damage is a known technology. By way of example: a Yamaha two stroke outboard motor I used at least a decade ago had an internal oil tank. In case the motor was out of oil it reduced the available power to avoid engine damage. I remember this as it happened to me while I was crossing a shipping lane. It was quite exciting for a while, as there was a largish ferry approaching a couple of kilometers away and I judged that if I failed in filling the tank I might not have enough time to get clear. As another example: automobile engine management systems may change to a different throttle response and ignition timing in case they lose some sensors feeding information regarding the state of the engine.

It is also common to have an indicator in the car that warns when the outside temperature is close to freezing. Several current models also offer systems that read speed limit signs with a camera and give this information to the driver. Information about automated speed traps can be downloaded to navigation devices.

Fusing all this information provided by these prior technologies is clearly necessary in an autonomous vehicle. It might be an invention if a novel way of doing this was shown, but is not enough to tell that there is a problem in need of a solution. To go back to my claim that this is what drivers do all the time; it might be an invention to show how to do, with a computer, what happens inside the head of the driver. This is because the prior knowledge on that is pretty much missing.

The description and figures are easy to follow, apart of some patentese which needs a couple of passes before being understood. Not much new is offered so the usefulness of the description to society is low. There doesn’t appear to be a step change from prior technology or knowledge so the invention is missing.

The claims are pretty straight forward and they clearly are derived from the description. Some elements seem to be missing though, like the idea where the vehicle checks in to a maintenance facility when it detects something in need of fixing. But this is likely well covered in sci-fi so it would not be new.

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