Shared Mobility Service With Mobile Statistics
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| Anzahl der Teile | 295 | |
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| Lizenz | CC-Namensnennung 3.0 Deutschland: Sie dürfen das Werk bzw. den Inhalt zu jedem legalen 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. | |
| Identifikatoren | 10.5446/43333 (DOI) | |
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00:00
ServerCASE <Informatik>StatistikBitSystemidentifikationAnalytische MengeStatistikSoftwareentwicklerServerAutomatische HandlungsplanungTypentheorieTabelleSpezielle unitäre GruppeZentrische StreckungVorlesung/KonferenzComputeranimation
01:03
Inhalt <Mathematik>ServerDatenanalyseTransportproblemFlächeninhaltMetropolitan area networkCharakteristisches PolynomWechselseitige InformationHill-DifferentialgleichungLokales MinimumÜberlastkontrolleDialektFlächeninhaltMAPTransportproblemAbstandEndliche ModelltheorieZahlenbereichSoftwareentwicklerMeterZweiVertauschungsrelationDatenbankGenerator <Informatik>CASE <Informatik>TopologieAnalysisTotal <Mathematik>SoftwaretestDigitalisierungForcingMultiplikationsoperatorStützpunkt <Mathematik>MagnetbandlaufwerkComputeranimation
04:00
Proxy ServerTelekommunikationSchnelltasteServerGeradeDifferenteMinkowski-MetrikKartesische KoordinatenAnalysisOrdnung <Mathematik>TransportproblemTwitter <Softwareplattform>CASE <Informatik>Leistung <Physik>
05:09
Zusammenhängender GraphProzess <Informatik>ReihenfolgeproblemPlastikkarteATMTransportproblemWorkstation <Musikinstrument>Arithmetischer AusdruckWellenpaketMetropolitan area networkTwitter <Softwareplattform>TermComputeranimation
05:28
TransportproblemATMVHDSLFlächeninhaltServerMultiplikationsoperatorComputeranimation
06:02
Workstation <Musikinstrument>Hill-DifferentialgleichungService providerTelekommunikationSystemplattformFlächeninhaltGreen-FunktionGruppenkeimRadiusServerService providerBestimmtheitsmaßQuellcodeCASE <Informatik>Mapping <Computergraphik>SystemplattformOffene MengeDigitale PhotographieComputeranimation
07:12
ZeitabhängigkeitATMVektorpotenzialÜberlastkontrolleFunktionentheorieDatentypZeitzoneProxy ServerKonditionszahlFlächeninhaltWorkstation <Musikinstrument>Nachbarschaft <Mathematik>BenutzerfreundlichkeitTransportproblemMinkowski-MetrikSystemplattformServerKontrollstrukturDifferenteGarbentheorieKartesische KoordinatenAnalysisStatistikRechenbuchMusterspracheGeschlecht <Mathematik>GruppoidTrennschärfe <Statistik>URLServerMultiplikationsoperatorTourenplanungInformationTransportproblemBildgebendes VerfahrenTeilbarkeitBus <Informatik>PlastikkarteMessage-PassingLokales MinimumAnalysisFehlermeldungProxy ServerService providerFlächeninhaltMinkowski-MetrikDichte <Physik>Automatische HandlungsplanungWorkstation <Musikinstrument>ZentralisatorInverser LimesAnwendungsspezifischer ProzessorFokalpunktTelekommunikationWasserdampftafelMereologieSchnittmengeVererbungshierarchieBestimmtheitsmaßOffice-PaketPhysikalischer EffektBeobachtungsstudieOffene MengeDivergente ReiheVierzigBenutzerschnittstellenverwaltungssystemRechenbuchWikiTopologieStatistikHilfesystemAggregatzustandMomentenproblemMetropolitan area networkMeterNichtlinearer OperatorComputeranimation
12:57
TelekommunikationCOMWCDMATotal <Mathematik>InformationstechnikStatistikZellularer AutomatTurm <Mathematik>ZeitzoneAdressraumMenütechnikTrägheitsmomentTesselationDistributionenraumServerStatistikWorkstation <Musikinstrument>Bus <Informatik>ZeitzoneStochastische AbhängigkeitZellularer AutomatDialektTurm <Mathematik>TesselationProzess <Informatik>InformationstechnikSmartphoneGenerator <Informatik>DistributionenraumGebäude <Mathematik>Disjunktion <Logik>TelekommunikationDarstellung <Mathematik>Trajektorie <Kinematik>Message-PassingRechenwerkMultiplikationsoperatorSoftwareCASE <Informatik>Quick-SortRechter WinkelPunktAdressraumProxy ServerSampler <Musikinstrument>MagnetbandlaufwerkBestimmtheitsmaßKreisflächeAggregatzustandSystemaufrufInformationsspeicherungMailing-ListeNichtlinearer OperatorOvalART-NetzSchnittmengep-BlockBeobachtungsstudieComputeranimation
18:43
StatistikSelbstrepräsentationRechnernetzWorkstation <Musikinstrument>SoftwareDichte <Physik>Zwei
19:14
StatistikZeitzoneMusterspracheBus <Informatik>PlastikkarteGeschlecht <Mathematik>Workstation <Musikinstrument>GruppenoperationMAPSoftwareStrömungsrichtungMultiplikationsoperatorAdressraumProzess <Informatik>InformationOffene MengeVorlesung/Konferenz
20:51
MAPDatenbankStrömungsdrosselPhysikalisches SystemSoftwareNeunzehnBenutzerschnittstellenverwaltungssystemVorlesung/Konferenz
Transkript: Englisch(automatisch erzeugt)
00:07
Nice to meet you. I'm from LHC corporation is providing affordable housing and Smart City and I'm very sorry because my title has a little bit changed it because the
00:21
there is some challenge issue about collecting data and the identification of the more The largest care data into this analytics so My final final title Is shared mobility service with the mobile phone data mobile statistics. It is it is not a
00:46
Developed city is a greenfield development. So it is a some approach about about planning and some some real estate development and and applying the this
01:02
statistics or by statistics and It is some special case for the Korea and very firstly first organizing City and we are some challenging issue of the committing and we providing some regional level
01:22
transportation and to substitute to some transport between the residents to the regional transportation hub, so the very Some Ten to thirty minute distance we I define that
01:42
First and last mile committee trip and so it is the very different from the traditional transportation demand analysis that is the transportation model is a start from the home base trip, but we cannot
02:01
Calculate or we cannot counting the number so instead we have a model but it is the narrow model but we using the database to Calculate the home base the trip so we can predict the post and last mile trip in the community level
02:22
We are we Korea is the very heavily populated Better person area then means more than Half of the population South Korean population live in the Seoul metropolitan area That is we can guess the Romanian whole total population is
02:43
20 million but Seoul metropolitan area only this area live 25 million people live in this metropolitan area So we provide we developed a new town development it is the
03:02
Eboligy area is centimillion-square meter and 30,000 over 30,000 household and we had some first and second generation new town and When we developed in new town, we provided some regional level transportation such as expressway and railway system
03:22
But it can fulfill the satisfaction of the commuter that means more long commuting trips just one hour on and a half hour almost two hour, so When I analyze the committee trip the first and or last mile
03:44
trip is almost 30 minutes, so if we minimize those trip then the Overall committee tree will be slightly Diminished than the existing trip
04:01
So we applying the Existing mode of transportation instead we apply we provide the shared mobility and it is some public Some space for the some shared mobility such as Uber and hailing application
04:23
services and also we provide The electronic keyboard like services from lime but it is either so a little bit different from the line because it's a newly developed and In generally in the old old town of Korean cities is very narrow
04:48
Pedestrian Workways, so it is very dangerous if we if we allowed this Personal mobility service and we have some analysis to provide some some
05:05
sharing facility we call this is sharing port and In the trend in the one mobility is some Diverspied mobility and Electrification is the new trend and in in this in this new town it is the
05:26
In this term This new town is the around the 30 kilometers from the CVD area so we provide we We Introduce
05:40
GTX high-speed railway system, but in Korea there are many railway subway system, so this is the very deep underground another railway system high-speed railway system and also first and last mile we Want to provide a shared mobility service?
06:05
And that in the Korean market is the very traditional is very Not a lot of open market that means so you have a very Isolated platform for the maps and
06:23
mobile services also in also in the mobility services also Also same situation so in Korea though taka mobility is the major Mobility service provider and also it's the interesting thing is the Hyundai
06:40
Hyundai with us also provide this kind of service. They are recently focused on the
07:10
photo low-income housing our focus of personal mobility is the The motorized motorized the transportation mode and
07:23
micromobility and smart personal mobility so it it belongs to This kind of device and with micro vehicle is also we are considering in but in in in Korea though
07:40
This this kind of lime service illegal so also there are in this especially kangnam You may heard about the kangnam in central area of Seoul there are some service provider of this kind of personal mobility service, but it is the Not a legal service, so if there is extant it cannot have some
08:06
It is not very difficult situation Anyway, so government has provided some Temporal permission to the some designated city and designated lane to a pilot city and
08:23
still there is some Insurance issue and on a license issue and a speed limit some some guys and They they are speedy meaty so over the Permitted speed so there are some many accidents in Korea
08:45
So in this in this city we want to provide this mobility as some Some paratransit and reducing commutative trip between the small interval and also and then that are
09:02
Over pick-time used as a little transportation and We introduced shared mobility service is personal mobility shuttle bus and only vendor service and also as a facility sharing port and Sharing protein is a shared device and facility and space and it's like this
09:27
and in the in the in the city we In the in the deep underground there is a railway system and on top of the railway station We adapt some sharing port and we
09:43
according according to some demand analysis and want to Select the location of the service and route and it is some imaging for future plan and The main main concept is the divide or pedestrian and biker
10:06
So to analyze this The Adapted into this service in the newly developed city We making data for the
10:24
Posting rest my service. That means it is the We calculating the from home to the station Railway station or bus stop and calculated or
10:41
travel time and route but route is the We cannot collect from the Telecom company because there is you cannot if we identify the Data the identified or its personal information and its location then it have to be
11:04
Aggregated so it it the data is the aggregated one as some so aggregated the pass and a Aggregated way so we have to instead we divide the time and more than
11:26
Ten minutes the minimum time we can collect is the five minute but five minutes have a very There are many errors so we have to extend the time to ten so
11:42
we are experimenting the collecting from ten to fifteen minutes every ten to fifteen minutes from the designated community So by doing so we can Collecting the people's movement, but it is already collected one
12:04
Minimum five a person in one minimum one one pass there Anyway, there are many passes is so it's in the city, but is the individual pass cannot be we are
12:22
Represented in in this map and and then we are then calculating Come to the combo to the trip to share the mobility and it is not we digital this step So we still in the calculating trip This is this is still a challenge issue and also after then we have we have to
12:44
using the special analysis to some density analysis to location and pass of the some reliable Passport to providing service that means not just providing services it is some
13:05
Building or exclusive lane for this service and we are using the mobile statistics and in Korea, they are a city a telecommunication company the The SK Telecom is the major company over 50% of all Cheryl come Cheryl Cheryl market and
13:28
in this company they they using the From 2g to 4g Technology to collecting data 2g 3d data and recently from 2015 collecting
13:44
4g data, so it collecting the CDL signal CDL signal from the only from the cell tower, but also signals from the 4g it is a Communicate
14:01
communication between every smartphone to the cell tower and then they are collecting the data and using this data to make some mobile statistics and Basically the mobile statistics is cell tower based generation and
14:23
The This methodology is collecting the signal data and the CDL data and we combine the daytime staying and nighttime staying and in the combined billing address and By doing so we can generate basically cell tower based data
14:45
But it is the cell tower based data is the basically tessellation of the each cell tower It is a big one, but each cell tower has the monitoring though. It's it's Sensitivity of a signal using the data we also
15:04
Dividing the more more greed-based The collecting collecting unit that is called a piece a piece a is 50 by 50 population data and Originally we use this kind of data to collecting the
15:23
population Is just a snapshot of data for every five every five minute, but it cannot it cannot Depict movement of people so we again go to the process to start a generation generation method of
15:43
Original destination that means it is not original destination It is the trajectory but many trajectory many kind of passes passes passes So we cannot make a data aggregate the data. So we are testing the
16:03
Efficient way of collecting data it is the right side is a traditional way of collecting mobile data and the left side is the company's the best sort of collecting data piece piece a piece a based collecting data and when the left side of
16:23
Collection collection zone then you cannot efficiently managing the it's original destination, so we Use your right side method and we were
16:40
Depine Depine define the Efficient way of collecting tone, so especially cell tower based tessellation is the regular Regular and uneven distribution according to only uneven distribution of a cell tower It is very hard to analyze data
17:04
and We first based on the we made a black according according to the road network and the first step of the collecting data from From original destination. They mean it is the one day and 24 hours. So
17:25
people starting blocked from the each zone and Stop at a bus station or the Train station and then go out to a final destination first status
17:41
origin starting point origin is that we calculate by 30 minutes stay in the designated time and then we if the In this case in this case case we have people's tub of or you visit some
18:01
designated zone for the station and regional bus stop then we check people is communicating in this cell tower but the Station is the independent the cell tower, but the bus station has don't has the
18:21
designated or independent cell tower, so the drone for collect collecting data for the bus station Joan is the larger than the station station Joan, so we after the after the post to collecting the data and then
18:44
we using the shortest path shortest path and we met the best one to network and it's it's the density and its destination on the road network and It is the destination in this new town destination to this
19:04
subway subway station and second one is another subway station and it is the full subway station we Adopted bus stop and Using using the bus card data and it's
19:24
The You see you see you see job cutter data and applying the some other Joan purpose and we the aligning the organizing the aggregation tone for
19:41
It is original Station railway station in is the bus station bus station is more than bigger and bigger than just Railway station So Currently we are making a iterative method to analyze the data and
20:06
the data data we are collecting the data is the origin and destination and travel time and using the billing billing address and billing information to
20:20
Subscribers age group and gender group So currently we are in this stage and we were developing the this methodology. Thank you Does anybody have any question?
20:45
Well, I do You have a question. Thanks very much Just a quick question on the which road network are you using for for the routing and things is it open street map or something else
21:09
With commercial data from the some navigation map The centerline data and we networked that data Okay, great. Thanks
21:22
What software do you use for developing this kind of system The first step is not a system but a database for analyzing this The Community community level the people's movement from home to their
21:44
Buses tab and the train station. So we are very detailed them detailed database for this commuting trip It's the first step. Yeah Any more questions Well, let's give an applause to
22:04
Choke Choke Choke and Samnida Thanks very much. And please continue enjoying post4g 2019 in Bucharest