Liikluse simuleerimine mobiilside võrkude logide genereerimiseks linnakeskkonnas
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2017
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Abstract
Viimastel aastatel on hakanud mobiilside andmestik paeluma aina rohkem teadlasi erinevatelt teadusdistsipliinidelt. Need andmed aitavad mõista inimeste käitumis- kui ka liikumismustreid. Mitmed mobiilsusandmestikud (nagu näiteks Call Detail Records mobiilside andmed) ning GPS andmed näitavad inimeste liikumissagedust ja -põhjusi.Need andmestikud sisaldavad endas väärtuslikku informatsiooni ühiskonna kohta. Töödeldud informatsiooni saab kasutada mitmel otstarbel. Teadlased saaksid andmestiku põhjal planeerida teedevõrgustikke, paremini suunata inimestele reklaame arvestades nende paiknemist, luua uusi positsioneerimistehnoloogiaid, arendada rahvastikukontrolli tarkvara jne.Vaatamata tehnoloogilistele võimalustele on inimeste mobiilsusandmestikud väga raskesti kättesaadavad, sest need on kaitstud riiklike regulatsioonide poolt, kuna riivavad inimeste privaatsust. Teine tegur on mobiilioperaatorite enda huvi luua inimeste mobiilsusandmetel põhinevaid kommertslahendusi. Selline situatsioon ei innusta operaatoreid jagama äriliselt vajalikku informatsiooni kolmandate osapooltega. Antud magistritöö käigus näidatakse, kuidas sellest raskest probleemist üle saada arendades mobiilsidevõrgukäitumissimulatsiooni prototüüpi. Genereerides andmeid läbi erinevate teaduslike liikumismudelite, mida võimaldab meile liiklussimulatsiooni tarkvara.Uurimistöö tulemusena selgus, et selline lähenemine on resultatiivne ja omab mitmeid laienemisvõimalusi. Täheldati mitmeid võimalusi koostööks teiste uurimisvaldkondadega, et muuta genereeritavaid mobiilsusandmeid reaalelule sarnanevateks. Mobiilsidevõrgu käituvussimulatsioon on näidanud suurt potentsiaali ning arendamise käigus avaldusid võimalused, mida algselt ei osatud oodata. Mainitud mobiilsidevõrgu käituvussimulatsioon on integreeritud eksisteeriva liiklussimulatsiooni tarkvaraga, mis on vabavara ning mida on võimalik laialdaselt konfigureerida. Liiklussimulatsiooni tarkvaraskasutatavad inimkäitumise mudelid põhinevad erinevate teadustööde tulemustel ning seetõttu mobiilsidevõrgu käituvus- ning liiklussimulatsiooni sümbioosi tulemusel genereeritud andmed on märkimisväärse väärtusega.
In the last years, the use of mobile phone data logs start to attract a lot of researchers’ attentions from various disciplines. Those logs help the scientist to understand and predict human behaviour. The mobility logs, like Call Detail Records and GPS data, show where to people commute, how often do they commute and, usually, those logs also say why. These logs hold knowledge about our society, from that data the knowledge could be extracted and used for multiple purposes. The scientists could analyse through the movement how to plan the road infrastructure, generate target advertisement based on forecasting peoples displacement, new positioning technology, population control software, etc. But there are limits on the people's mobility data. Those information logs are heavily protected by the government privacy data laws to protect the personal rights. Additionally, the mobile operators are interested in their own commercial solutions and therefore their interest to share vital information is low. Here, in this thesis, we show that this cumbersome problem can be over-stepped by prototyping a cellular network behaviour simulator to generate the logs for us through different scientific commuting models inherited from the traffic simulation program.The result of this thesis reveals that this approach is feasible and shows multiple expansion possibilities how to produce even more real-life like mobility logs. The development of the cellular network behaviour simulation has shown huge potential and even bigger possibilities than predicted in the beginning. Since, our cellular network behaviour simulation is integrated with already existing open-source, highly configurable, road traffic simulator basing on the scientific human behaviour models produce with considerable value data.
In the last years, the use of mobile phone data logs start to attract a lot of researchers’ attentions from various disciplines. Those logs help the scientist to understand and predict human behaviour. The mobility logs, like Call Detail Records and GPS data, show where to people commute, how often do they commute and, usually, those logs also say why. These logs hold knowledge about our society, from that data the knowledge could be extracted and used for multiple purposes. The scientists could analyse through the movement how to plan the road infrastructure, generate target advertisement based on forecasting peoples displacement, new positioning technology, population control software, etc. But there are limits on the people's mobility data. Those information logs are heavily protected by the government privacy data laws to protect the personal rights. Additionally, the mobile operators are interested in their own commercial solutions and therefore their interest to share vital information is low. Here, in this thesis, we show that this cumbersome problem can be over-stepped by prototyping a cellular network behaviour simulator to generate the logs for us through different scientific commuting models inherited from the traffic simulation program.The result of this thesis reveals that this approach is feasible and shows multiple expansion possibilities how to produce even more real-life like mobility logs. The development of the cellular network behaviour simulation has shown huge potential and even bigger possibilities than predicted in the beginning. Since, our cellular network behaviour simulation is integrated with already existing open-source, highly configurable, road traffic simulator basing on the scientific human behaviour models produce with considerable value data.