New Navigation App 'Live Roads' Promises 1.5m-Accuracy With Standard Cellphone Hardware (arstechnica.com)
Jonathan M. Gitlin from Ars Technica reviews a new navigation app called Live Roads, which promises 1.5m-accuracy via your current smartphone without the need of any extra hardware. In a nutshell, the app provides more accurate mapping/navigation than what's currently available via Google Maps or Apple Maps, but it's still not quite as accurate as a true "HD map." HD maps are accurate to within a centimeter or two and are usually made by a combination of traditional surveying and lidar scanning. Here's an excerpt from the report: A few weeks after talking with the company, I was delivered a Samsung S7 loaded with Live Roads. I'll be honest: I'm not that familiar with Android, and this isn't really a review of the app. I used it enough to check that it does what it claims, but I didn't use it as my sole method of navigation. However, this brief bit of user-testing did let me check out the claims in that email. I don't think I'd equate the app with the HD maps that autonomous vehicles will need. For one thing it's readable by a human being; for another it's not quite that accurate. But the spatial resolution was indeed better than it should be on a consumer phone, and Live Roads was able to locate me down to a specific lane on a multi-lane road. Various navigation apps give you lane-specific instructions -- for instance, telling you to stay in the middle two lanes if you're approaching a complicated intersection. Where Live Roads differs is that it can also tell which lane you're actually in. Whether this is enough of a feature to build a business model around is an open question; I'm quite happy using Google Maps on iOS, with occasional forays into Waze (running in the background to warn of speed traps) and Apple Maps (if I'm driving something with CarPlay and the infotainment's built-in navigation sucks).
But it left me wondering: how does it work? Paul Konieczny, CEO of Live Roads, gave me an explanation -- up to a point. "Primarily it is based around sensor fusion and certain probabilistic models -- we call it the Black Box," he said. "The current release of the app that is available in the Play Store has an earlier revision of our Black Box. This initial version is missing some of the functionality of the full-fledged system and thus has a spatial resolution of ~2.5m. This compares favorably to standard GPS that has a resolution of 4.0 m+." By summer, Konieczny hopes that the system will be fully operational and that accuracy will be down to under 1.5m. Assuming a large enough user base, that should let it offer lane-specific traffic data, "as well as introducing an entire ecosystem of 3D objects that users will be able to interact with," he told me.
But it left me wondering: how does it work? Paul Konieczny, CEO of Live Roads, gave me an explanation -- up to a point. "Primarily it is based around sensor fusion and certain probabilistic models -- we call it the Black Box," he said. "The current release of the app that is available in the Play Store has an earlier revision of our Black Box. This initial version is missing some of the functionality of the full-fledged system and thus has a spatial resolution of ~2.5m. This compares favorably to standard GPS that has a resolution of 4.0 m+." By summer, Konieczny hopes that the system will be fully operational and that accuracy will be down to under 1.5m. Assuming a large enough user base, that should let it offer lane-specific traffic data, "as well as introducing an entire ecosystem of 3D objects that users will be able to interact with," he told me.
I think he meant precision.
The good stuff is coming really soon...
Paul Konieczny, CEO of Live Roads, gave me an explanation Sensor fusion blah blah probabilistic models blah blah black box.
I'm disappointed that it didn't involve any AI Assistants or Cloud Services.
Some quality journalism from Ars Technica:
I'll be honest: I'm not that familiar with Android, and this isn't really a review of the app. I used it enough to check that it does what it claims, but I didn't use it as my sole method of navigation. However, this brief bit of user-testing...
So he can't use Android and he couldn't be bothered actually testing the app before writing the article?
... an entire ecosystem of 3D objects that users will be able to interact with ...
I already have an entire ecosystem of 3D objects I am trying not to interact with while I am driving.
Starships were meant to fly, Hands up and touch the sky - Nicky Minaj
"as well as introducing an entire ecosystem of 3D objects that users will be able to interact with,"
Tesla's already come with that.
Garmin was using this exact 'technology' 18 years ago.
And hence forth has Apple and Google.
What a fucking shit for brains submission.
What happened to Slashdot.
You can get a better GPS fix by having a base station at a surveyed point, but this isn't what they're doing, because it would be expensive. There are also corrections you can do based upon atmospheric conditions, but they say that wasn't good enough. They pretty obviously don't want to say how they're doing it, which makes sense for trying to corner the market. But I wonder how novel their methods are, and if they can really stay ahead for long.
They say it's by "sensor fusion" and probabilistic models. The sensors are presumably the accelerometer and maybe the barometer in a cell phone. They could have an idea of the nominal error of a sensor based upon the model of phone. The probabilistic models, I can only guess, come from having many users running the app at once so they can try to reduce the error using many measurements.
Once they narrow the precision of the fix to the size of a lane of traffic, they could start identifying the lane by the behavior of clients in that lane -- if everyone turns off the freeway at this point in this lane, it's probably an exit lane, that sort of thing. And those rules could become much more complex. Like, use a machine learning process and train it on a bunch of well-defined traffic situations.
But, two questions: first, can they compete with companies like Garmin and Google who have tons of money and clients, plus smart people who could try to reverse-engineer these improvements and roll them out basically for free? It could easily be worth it to crush competition. And, if the success of the probabilistic model is based upon having many clients, do they get this level of improvement everywhere, or only in higher-traffic areas like cities?
its simply GPS fused with other sensors and thats it...
GPS/GLONASS since Android 7.0 (i.e., Nougat), users now have access to raw GNSS measurements – opening the door to higher-accuracy
google maps even does this by asking you to accurately calibrate your compass
the problem is the antenna on most smart phones is terrible compared to those fitted in cars plus the ability for a car to accurately predict that your actually in a car compared to the smartphone which cant know this for sure...
Call me skeptical.
90% is keeping maps up-to-date. What good is 1.5m accuracy, if you encounter a road construction detour just constructed yesterday? Google Navigation works so well not because of its accuracy, but because they put so much time, money, and effort into updating their maps constantly. Even then, it's not hard to find examples of locations where Google Navigation is not quite up-to-date. Good luck "Live Roads"!
I use osm free maps and it pegs right to the parking spot I'm in, and as device is in front of the car, it shows close to front center of the spot. How is this special???
might be good for the US system but the European system has 1m resolution for public receiver and 1cm for military.
1.5m has not been considered good since years.
Is this class signaling? A disclaimer in case someone mistake you for Android trash and not the awesome Apple bro you actually are? Because I can't imagine anyone supposedly "from Ars Technica" finding themselves mystified by anything on a modern Android device. That just doesn't compute.
Maw! Fire up the karma burner!
My 2016 cellphone has that via differential GPS plus Inertial sensors, and is down to 1 foot accurate. I use it for mining spot location all the time.
Still waiting on Serviscope_minor to wake up to fucking reality and realize that Jessica Price isn't going to fuck him.
That data can be really useful to automatically find illegal lane changes (e.g. overtaking over barrier lines, pushing into queues over lines that indicate that you can't, turning from lanes that it is not allowed)
Yes, but can we be sure of his velocity?
I am armed because I am free. I am free because I am armed.
There's a lot of negative things to be said about Google Maps and Waze, but I can't say I've ever had a problem with accuracy that wasn't a half a second blip that was completely irrelevant to the current navigation: e.g. Maps has problems recognising I merged into a tunnel and then blips back onto another road for a second before correction.
Whoop-de-do.
My home built attack drone project.
What happened to this Broadcom GPS chip using L1 and L5 with 30cm accuracy? It was reported to be in 2018 flagship phones but I've heard nothing since the press releases last year.
http://gpsworld.com/big-news-from-broadcom-30-cm-positioning-for-consumers/
The accuracy commitments do not apply to GPS devices, but rather to the signals transmitted in space. For example, the government commits to broadcasting the GPS signal in space with a global average user range error (URE) of 7.8 m (25.6 ft.), with 95% probability. Actual performance exceeds the specification. On May 11, 2016, the global average URE was 0.715 m (2.3 ft.), 95% of the time. GPS Accuracy
User accuracy depends on many factors in addition to range accuracy, so the result is GPS Accuracy Levels it is possible now to get very accurate positions now, with differential GPS.
The really big change is that less expensive hardware is now able to handle the more complex math, and it is getting to market. Global Positioning System: The Mathematics of GPS Receivers
This is nothing new. Quadcopters have been doing this kind of accelerometer/barometer/gps sensor fusion for years, with better than 1.5m accuracy.
1-3m accuracy isn't actually better than the EU's Galileo constellation which will be fully functional in the next 2 years. The recievers for that are already in flagship android models, and by the time its fully functional (~2020) most phones will have it. Galileo is accurate to 1m and if you pay for it, 1cm.
I call BS on the explanation ... those "probabilistic methods" are already implemented by most navigation programs, placing you not at the location of the GPS lock, but on the nearest street considering direction of travel. ... even street cutoffs typically do not need to be down to that scale ...
Also, who needs 1.5m accuracy for navigation? I've not had any destination that required me to be exact down to anything less than 5m
Now, if they can spit out the coordinates actually down to 1.5m repeatedly for the same location, with me moving more or less erratically in between, and the program being stopped and started again, I will concede my argument ...
Didnt notice any improvement in accuracy. And the UI/UX were horrible. Plus the app repeatedly froze or crashed. This is not even beta software. Feels like an early alpha.
But their technology only requires a single drop of blood to achieve this level of precision!
If you don't know where where you are going, don't go. If you don't know where you are, sit down. If a problem comes along, you must whip it.
The PTB won't be happy until they can tell not only where you are and who you are (by your cell phone data), but also who you sat next to on the bus and who rode with you in your UBER or car pool. Were you in the front seat or back? It all goes into your dossier.
Just tried to install, and "this app is incompatible with all your devices". If it won't work with a OnePlus 5 running the latest Android 8, or the many Nexus devices I have, exactly what does it run on? PowerPoint?
I'm not really sure...I think it may be you who doesn't know what those terms mean. Accuracy is how close your measurement is to the correct value. Precision is how much variance you have between multiple measurements. This article talks about being able to identify correctly which lane you are actually in, which sounds like accuracy to me.
I assume in the process they are also increasing precision of the readings, too. They are probably cross referencing accelerometer and compass data with high resolution map data over time. Doing things like noting when you make a 90 degree turn, that you must've been in the center lane or right lane at that time and using future accelerometer readings to track future measurements relative to the guessed lane. This would result in multiple readings of the same position to reach the same determination of your specific spot, which would be increased precision. But that is just a side effect of the goal to improve accuracy.
Because.... in this case, some one could provide their readout of location to 20 decimals. Incredibly precise!
And, be off in real location by 300', so, not very accurate.
Idiot, an app is an app, no matter the platform. The added bonus with android is you probably have a back button!
Tired of my customary (Score:1)
Atia, M, Hilal, A.R. (Allaa R.), Stellings, C. (Clive), Hartwell, E. (Eric), Toonstra, J. (Jason), Miners, W.B. (William B.), & Basir, O.A. (Otman A.). (2017). A Low-Cost Lane-Determination System Using GNSS/IMU Fusion and HMM-Based Multistage Map Matching. IEEE Transactions on Intelligent Transportation Systems. doi:10.1109/TITS.2017.2672541
Some of the error in GPS measurements of closely located receivers is correlated. There is more information in the relative measured location of two units than in the absolute measured position of one. (Differential GPS is based on this: an accurate measure of a receiver's location is made by comparing its relative position to a known receiver location.)
So... rather than estimating the location of each user independently, maybe they fold in the relative position of each user and solve their positions jointly. Or put another way, the systematic error in the users' direct GPS coordinates might be estimated jointly rather than independently. In this way any other information used to more accurately locate individuals could be combined together to the benefit of all.
Handheld GPS receivers pre smart phones were already accurate within 3 to 6 feet with good satellite coverage. I had already assumed smart phones were even more accurate with cellular triangulation assist and being able to download real-time correction data online. I know when I look at Google maps with the satellite image layer turned on, it's always pretty damn spot on to where I am actually at.