Landmark Based Path Planning with a Linear Map Display For Mobile Map Applications
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| Anzahl der Teile | 183 | |
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| Lizenz | CC-Namensnennung - keine kommerzielle Nutzung - Weitergabe unter gleichen Bedingungen 3.0 Deutschland: Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben. | |
| Identifikatoren | 10.5446/32010 (DOI) | |
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| Produktionsjahr | 2015 | |
| Produktionsort | Seoul, South Korea |
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GeradeCASE <Informatik>Rechter WinkelEndliche ModelltheorieBitAutomatische HandlungsplanungInformationRichtungRoutingAttributierte GrammatikOrientierung <Mathematik>Notebook-ComputerSchreib-Lese-KopfAdditionFunktion <Mathematik>KnotenpunktKartesische KoordinatenAbstandSommerzeitPuffer <Netzplantechnik>SondierungAlgorithmusGewicht <Ausgleichsrechnung>ZahlenbereichEin-AusgabeZählenParametersystemGraphfärbungDomain <Netzwerk>QuadratzahlRechenbuchMobiles InternetPortabilitätGreen-FunktionMultiplikationsoperatorDichte <Physik>MereologieQuick-SortOrdnung <Mathematik>StandardabweichungServerBildverstehenKreisflächeRandomisierungGruppenoperationZellularer AutomatEreignishorizontGenerator <Informatik>RelationentheorieVorhersagbarkeitDivisionInhalt <Mathematik>Kategorie <Mathematik>CMM <Software Engineering>PunktArithmetisches MittelEuler-WinkelComputeranimation
07:24
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StandardabweichungDeskriptive StatistikKomplex <Algebra>t-TestQuick-SortPhysikalisches SystemCoxeter-GruppeSoundverarbeitungFokalpunktFlächeninhaltDichte <Physik>EreignishorizontEntfaltung <Mathematik>BeobachtungsstudieKategorie <Mathematik>DatensatzParametersystemGebäude <Mathematik>IntegralBitrateBitSoftwareschwachstellePunktAdditionKartesische KoordinatenModelltheorieBildverstehenStandortbezogener DienstMultiplikationsoperatorMatchingEndliche ModelltheorieVollständigkeitBenutzerprofilSchwingungAbstandRadiusZahlenbereichsinc-FunktionSoftwareentwicklerInformationServerDivisionLesen <Datenverarbeitung>Notepad-ComputerGüte der AnpassungMAPBridge <Kommunikationstechnik>Mapping <Computergraphik>UnternehmensmodellGruppenoperationTopologieKontextbezogenes SystemURLPaarvergleichRoutingSondierungCASE <Informatik>Profil <Aerodynamik>AlgorithmusMaschinenschreibenGrenzschichtablösungComputeranimation
22:04
Computeranimation
Transkript: Englisch(automatisch erzeugt)
00:04
Thank you. Good morning. We are here to present our research work. And we are from Sri Lanka. If you don't know Sri Lanka, this is where it is, in case you missed it. We are undergraduates and it's our first time presenting in our World Conference.
00:22
So please pardon us if you get a little bit nervous. I need you to take a look at that picture. It doesn't make any sense. It's just some lines connected to each other. Actually it's a raw notebook but it doesn't make quite much sense. But what if I placed something like this?
00:43
Now it does make some sense, right? Now we understand what this is. So what I placed were landmarks. Just keep that in mind and we'll move on with our presentation. Ma'am, if you mind, can I have the microphone? You have the microphone. I actually want to.
01:01
Okay, you are nervous. I switch on for you. Thank you. So this is how we're going to conduct our session. Okay. Okay, navigation. Navigation, simply put, we just travel from one place to another using a well-planned route. So it's not a new thing.
01:22
We have been navigating for like millions of years. So if you want to get to a destination for an unknown destination, what comes to your mind? Probably an aid of navigation or application which outputs you. A path or a text base or audio base or something.
01:42
Or you can just ask somebody for directions. But will we compare two outputs of this? We'll see. So for an example, if we get an output from navigation or tool, it will say something like this. Turn slightly to left in 7.1 kilometer to Aradhapur and Kamali. Both great cities, if you visit Sri Lanka, please come.
02:03
And in person, if we ask turn to left in Aradhapur Junction in like 7 kilometers, it's a four way. So there's something missing, right? There's something additional. So I have highlighted that. So what are these highlighted things? Those are landmarks. So that's very important.
02:20
People are used for navigation, people are used for landmarks in navigation that much. So why can't we close the gap? Why can't we integrate these landmarks not only for viewing but in path planning? So that is our motivation. So having that, we followed some problems.
02:41
First, we didn't have a good model to support the landmark based path planning. And then we had to collect the landmarks in Sri Lanka. So that's another problem. And then even if we do have visualizing in a small screen like this would be really congested. So you will have to zoom in and toggle around.
03:01
So that's another thing we encountered. So our solution, all you guys, we are creating a mobile web application which is cross platform and first base. And addressing those above mentioned problems individually. We are going to give more weight on those two solutions because that's what our research paper is about.
03:24
Let's get in detail about the landmark model. We had to create a landmark model because we are considering the significance of landmarks when path planning. So we had to consider some, we found out some attributes that make a landmark significant.
03:42
With our literature and the survey conductor. So the attributes were height, the spread, the daylight visibility and the cultural significance and the social significance. So these attributes were found out by the literature survey we have conducted and the research and the survey in Sri Lanka.
04:02
And I'm not going to go in detail much because now we have the model. We say we have the model now. So we will see how we are going to use it in path planning. So let's say we want to travel from A to B and we have two roads. First in black color is the shortest path and other one might be slightly longer than 2 or 3 kilometers longer than that.
04:25
So if it's a known domain what would you choose? Obviously the shortest one, right? But let's say you come to Sri Lanka. What would be your concern? Is it about cutting cost or not getting lost? So I would say it's not getting lost in an unfamiliar route.
04:41
So it's easier if you have many landmarks along the road to navigate on. To keep the confidence in. So we additionally wanted to take that landmarks into consideration in path planning at that place. So existing navigation applications what they consider mostly is the distance.
05:03
But we consider the landmark count along a path and also the significance of these landmarks. Because some landmarks might be not significant enough to be used in path planning. So we have calculated, we have taken two additional parameters.
05:20
Additional to distance and then we have passed it to dash square algorithm for calculation of the best path. And now we have the model and talking about, Bo mentioned two parameters in detail. The landmark count. It's much more easier to navigate on a road that has many landmarks rather than a road which has less number of landmarks.
05:42
So we counted the landmarks using a landmark buffer. The landmarks which are inside the buffer will be taken into consideration. And then we have taken the density of it and according to a weighted model we have got the impact of the landmark count. So that's how the landmark count weight is taken.
06:03
And then this way comes the above mentioned five attributes I mentioned in creating the landmark model. The height, the spread, visibility and culture and social significance. So we have taken the user inputs from the users and these are the values. And according to the values again we have weighted these attributes.
06:25
And we can get a weight on it. So now let's say we have a model and then we have used it in path planning. And now let's see how we are going to show it in a small mobile screen. So what I want to tell you is, now let's say we are travelling from A to B.
06:43
And we are taking major, I have circled in green colour major turns you make. One for the right and the other for the left. So between these two, now basically what you are doing is you are not deviating from the path. What you are doing is you are just going along. So what's the purpose of showing this? So we thought of it like it's quite unnecessary information when it comes to small mobile screens.
07:06
Showing the bends and all. So we wanted to make it linear between the turns. So that's what we came up with for linear path. So if you put for example something like that would be the output, the turns.
07:20
And the significant landmarks around it will be shown. And if you want to navigate the heading, the orientation will be calculated according to the heading. So that's how we solved the problem when it comes to smaller mobile screens. But we can't do any of this. If you don't have enough landmarks.
07:43
So how are we going to get landmarks? We allowed the users to place landmarks on us. But nobody would come and just place landmarks on our application. So we had to keep them interested. So that's why we inherited the socialising concept. Which you can keep in touch with people you want to.
08:02
And you can call a leader, you can update the status. And you are given a rating according to the number of landmarks you have placed. So to keep them interested so that they will contribute to our application. And also we are creating the model OSM compatible so we can contribute to it as well.
08:22
So to move on with the demo and the rest of the presentation I'll invite my colleague. Thank you. Thank you. Now all concepts have been explained. So let's see the system architecture of the application that we have developed in order to achieve our research targets.
08:45
From our application the users can use our application to navigation purposes. Or to socialising purposes using our mobile web application. Which will communicate with our application servers. We have a web server, a map server and a file server.
09:02
And our backend which has a special database as well as a non special database. Feeds data into the servers and those two communicate and get the job done clearly. So as you can see in socialising the normal socialising things like adding, removing friends, searching friends, updating status.
09:26
All those can be seen. And in navigation, landmark addition, removing and linear path and the best path is here. So if we talk about the technology stack. We have used OpenLayers 3 and jQuery Mobile as our front end implementation.
09:43
We use OpenLayers 3 as our map viewer and jQuery Mobile for UI implementation in the front end. Which is more friendly to mobile devices. And when it comes to servers we use GeoServer as our map server and Apache as our web server and PHP as our server style language.
10:01
When it comes to the backend we use PostgreSQL database to feed OpenStreetMap data as the basic data set into the PostgreSQL database. And we use PG routing extension to enable routing algorithms in it. And we use PostG capabilities to perform specific special functions.
10:23
And using PG routing capabilities we use wrappers. You know our own wrappers using PG routing functions as well. Now let's see our demonstration. Now this is how user will place a landmark. Let's say he places a landmark right here.
10:43
So these are the attributes that we are talking about. These are categories. Now let's say the place of worship. Then he will have to select a region. So why do we have to select a region? Because we should address local context when it comes to a landmark model. Because in a country like Sri Lanka there are like varieties of regions.
11:03
So we should address that as well. And obviously a landmark should have a name and address. The longitude and latitude will be captured according to the mouse click. And these attributes right here. Height, height, visibility.
11:24
And text are used to identify the social significance and the cultural significance. As well as to create the landmark icon right here. And stand out means how spread the landmark is. Does it stand out from the rest of them?
11:42
So we have our landmarks. So let's see how path planning goes. Let's say we use a start and a destination. This is around our university. So two paths are given for you. One is the shortest path and the other is the best path. So the shortest path is using the normal distro algorithm in PG routing.
12:03
You can see it's 6.03 kilometers while the best path is 7.40 kilometers. So best path is slightly longer than that. But if you see closer, this shortest path. You see you know short path. This shortest path takes a by path around here.
12:23
Like a shortcut. So during this terrain the user can get lost. Because it's not a main road. It's a small road. So if you are unfamiliar about it, you may get lost. But when it comes to the best path, it has a set of landmarks. And you are always travelling in the main path. And you have landmarks to assist you.
12:42
During turns and during deviations. And you can get to your destination easily. As you can see it follows the main path most of the time. So that is our solution for the best path. Now let's see about the linear path. We take this best path into consideration when clearing the linear path of that.
13:03
So what have we done here? We have omitted the bends that the best path had between the turns. And made them linear so that users will only see the turns to make. And all the other times he will be travelling straight.
13:20
So when he wants to turn, he will have landmarks to assist them as well. So that's our linear map. Now let's see our geo-socializing concept. When a user is logged in, the map is centered to his origin. And you can see there are two radiuses on it.
13:42
These two radiuses, the smaller one is the aqueous radius. As you can see it has less accuracy because by taking the video the laptop didn't have an accurate location of reading. The other one is the proximate radius.
14:00
That's what we are more concerned about. This is about the accuracy of the location that you are in. This proximate radius means how long, let's say, We can choose the radius of the circle that we need our proximity circle.
14:21
So as you can see if we extend it to 2 kilometers, we can find our friends around 2 kilometers around us. So let's say he needs a ride and he is like 1 kilometer around me. So if I am going on the same road, maybe I can give him a lift.
14:41
So these things can be achieved by using this concept. And as you can see the users are being shown in the map with their status on it.
15:01
Now let's see about our user profiles. The user profile has a separate user profile for each user when they register themselves. They can update their status. And of course you can call them if you need. Let's say I pick him up like that. We can contact him using this application.
15:23
So this is the social aspect. He can update his own profile. This is the rating that we provide the users with respect to the number of landmarks they have contributed to the collection. And he can put offline as well if he doesn't need to be seen in the map.
15:41
Some people have issues in that. So you can see friend requests, update status and those stuff as well. So let's have a comparison about this. As my colleague mentioned, this application which we have developed to achieve our research targets for under two categories. The navigational applications and the location based social networks.
16:04
When it comes to navigational applications, most of the applications like Google maps, OSM use shortest path. But in our case we use our optimum path. We have shortest path as well. We have optimum path which considers distance as well as landmarks.
16:21
And we have a linear map as well. When it comes to geosocializing, there are applications like Foursquare, Fire My Friends. They are location based services. But this proximity radius concept and keeping touch with friends is in our application as well.
16:40
In optimum path, how we achieve that is if you have any doubt like Let's say you may know the PG route in distro algorithm. It has a cost parameter. We create a cost column of our own using our weighted models. And create that cost column as our cost parameter.
17:05
So the future of our research. So we are conducting an ongoing survey to consolidate the weighted models. So that at the completion it will be a perfect model. Like a user tested model which will have more accurate readings.
17:22
And we will have to enable navigation on the linear path as well. Which is been working on in another couple of months. We will be able to do that. So acknowledgement. We are very thankful for the Phosphogy committee. They have provided us with a travel grant to participate in the Phosphogy conference.
17:41
And our study is initiated by the Geoinformatics research group. And of GeoLab of Sri Lanka Institute of Information Technology. And it is now supported by a research grant as well. So that's the end. And let's combine our natural behaviors with the technology these days.
18:02
Thank you. If you have any questions. Okay, so thank you also for this presentation. Questions? Questions? Come on. Questions also for them. Yes.
18:20
Thank you for the presentation. I may have missed that. But have you also considered geographical landmarks in your system? Like mountains or rivers? We consider trees, rivers and bridges. Yes. Yes.
18:40
Yes. Yes. Yes. And then a question from the other competitor. You said that users can add their own landmarks at their own discretion.
19:04
So what would stop them from adding something as a landmark that might be specific to a community? It's a landmark in the community but not a landmark to the rest of the city. Like let's say now we have created the model more compatible to the Sri Lankan context.
19:22
So that is one of our main concerns in Sri Lanka. There are like four communities. So we should support all the four communities. And let's say the best example is like religious trees and religious places that we have. So let's say Muslims visit mosques and Buddhists visit temples and Christians visit churches.
19:45
So like that we should address all the community needs as well. Other questions? No, I have just a comment. Because when I go around in a city that I don't know, generally I look for shops.
20:07
I'm joking but the idea of profiling the kind of user is very useful because probably you can notice some things and another person can notice other things.
20:21
That is the first point. But with respect to shops, I was not joking really because you can have some landmarks coming from owner of shops asking them also to contribute by paying as more fees every year. Suppose that they pay a small fee every year for having the shop advertised in your application as a landmark.
20:49
And if they don't pay the small fee, they will be removed. Actually we have. Be useful for everybody and give sustainability to your system. Actually we have our own business model and we have planned that also.
21:03
But we didn't include that here because it's more research. We have location based notifications to aid us in. If you look for landmarks, you have generally the owner of shops want to provide this kind of information. And really when the advertisement of shops on the road is something that you can see.
21:26
So yes, there are churches and so on. But there are also shopping addicted people. The last question comments.
21:41
Nobody has nothing to say. So are you happy about this session? I'm very happy because it was a very nice session. All of you are very, very excellent students and I suppose future researchers. So now it's very difficult to decide about you.
22:01
So thank you. Thank you also for the floor. And go to the next session please.
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