Methods for Inferring Route Choice of Commuting Trip From Mobile Phone Network Data

Sakamanee, Pitchaya; Phithakkitnukoon, Santi; Smoreda, Zbigniew; Ratti, Carlo

doi:10.3390/ijgi9050306

Cited by 16 publications

(20 citation statements)

References 41 publications

(38 reference statements)

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“…These losses are due to fading and multiple propagations [33]. From the studies, it has been concluded that the range of the excellent signal is between 0 and −60 dB m and for the poor signal is above −100 dB m [34], as shown in Figure 2b. The goal of the suggested research is to figure out where the best cell phone tower placement is.…”

Section: Introductionmentioning

confidence: 91%

A Novel Method to Determine the Optimal Location for a Cellular Tower by Using LiDAR Data

Bharadwaj

Dubey

Zafar

et al. 2022

ASI

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The cellular industry faces challenges in controlling the quality of signals for all users, given its meteoric growth in the last few years. The service providers are required to place cellular towers at the optimal location for providing a strong cellular network in a particular region. However, due to buildings, roads, open spaces, etc., of varying topography in 3D (obstructing the signals) and varying densities of settlements, finding the optimal location for the tower becomes challenging. Further, in a bigger area, it is required to determine the optimum number and locations for setting up cellular towers to ensure improved quality. The determination of optimum solutions requires a signal strength prediction model that needs to integrate terrain data, information of cellular tower with users’ locations, along with tower signal strengths for predictions. Existing modeling practices face limitations in terms of the usage of 2D data, rough terrain inputs, and the inability to provide detailed shapefiles to GIS. The estimation of optimum distribution of cellular towers necessitates the determination of a model for the prediction of signal strength at users’ locations accurately. Better modeling is only possible with detailed and precise data in 3D. Considering the above needs, a LIDAR data-based cellular tower distribution modeling is attempted in this article. The locations chosen for this research are RGIPT, UP (45 Acre), and Shahganj, Agra, UP, India (6 km2). LiDAR data and google images for the project sites were classified as buildings and features. The edges of overground objects were extracted and used to determine the routes for transmission of a signal from the tower to user locations. The terrain parameters and transmission losses for every route are determined to model the signal strength for a user’s location. The ground strength of signals is measured over 1000 points in 3D at project sites to compare with modeled signal strengths (an RMSE error 3.45). The accurate model is then used to determine the optimum number and locations of cellular towers for each site. Modeled optimum solutions are compared with existing tower locations to estimate % over design or under design and the scope of improvement (80% users below −80 dB m improves to 70% users above −75 dB m).

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Section: Introductionmentioning

confidence: 91%

A Novel Method to Determine the Optimal Location for a Cellular Tower by Using LiDAR Data

Bharadwaj

Dubey

Zafar

et al. 2022

ASI

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“…Most contributions of the work revolve around the representation of mobility and impact analysis. Experimental results show that it is possible for gathering route choice information on a large-scale road network based on route choice inference models for digital trace collection [27]. As Cats and Jenelius demonstrated, real-time information could facilitate the understanding of transport networks' vulnerability and disruptions [259].…”

Section: Impact Of Mobile Technology On Transport Systemsmentioning

confidence: 96%

Mobile Technology and Studies on Transport Behavior: A Literature Analysis, Integrated Research Model, and Future Research Agenda

Sun

Liu

Zhang

2021

Mobile Information Systems

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The prevalence of mobile technology has been significant in transport research. Despite a growing application spectrum of smartphone uses and interests in mobility inference, little effort has been put into discussing theories, models, and research topics based on a systematic study of scholarly sources rooted in the interdisciplinary area of mobile technology and transport. Therefore, a timely and comprehensive synthesis of the current state of research is deemed to be required. A literature analysis, following PRISMA guidelines, aims to identify the successful development and implementation of the mobile technology that can be employed for behavior studies in transport. A review of the Web of Science Core Collections, JSTOR and SAGE databases, is performed. A rigorous screening process is used to collect key articles to construct the general image of existing knowledge. In addition, this study suggests an integrated research model to summarize how previous studies attain behavioral outcomes and a research agenda to identify unresolved research questions that future research can address. Two hundred fourty-eight papers meet the inclusion criteria. This study demonstrates that mobile technology is helpful for a better understanding of the various types of transport behaviors. They can be categorized according to their system designs and research topics: (1) Smartphone apps in sustainable transport and travel planning were studied in a remarkable collection of articles. (2) As individual’s mobility was under question, cellular signaling data were prominent for the formulation of analytical models. (3) CDRs, WiFi, and GPS data have increasingly been used, but the share of the modeling techniques for all mobile information systems has remained low. It shows that system designers could supply more desirable and appealing features in most areas. However, applications for the movement of goods are limited, although freighting has moved toward digitalization.

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“…Apart from investigating commuting behaviours and measuring the commuting distance, a commuting map also helps us to understand commuting patterns [35]. A flow map is a typical way of visualising the work-to-home journey, and it has a wide range of applications such as transportation flow and commuting flow [36][37][38][39][40][41]. Tobler [42] presented some early examples of the initial flow map to show geographical movements.…”

Section: The Origin-destination Flow Mapmentioning

confidence: 99%

Understanding the Spatial Effects of Unaffordable Housing Using the Commuting Patterns of Workers in the New Zealand Integrated Data Infrastructure

Xiong

Cheung

Filippova

2021

IJGI

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Commuting behaviour has been intensively examined by geographers, urban planners, and transportation researchers, but little is known about how commuting behaviour is spatially linked with the job and housing markets in urban cities. New Zealand has been recognised as one of the countries having the most unaffordable housing over the past decade. A group of middle-class professionals called ‘key workers’, also known during the pandemic as ‘essential workers’, provide essential services for the community, but cannot afford to live near their workplaces due to a lack of affordable housing. As a result, these key workers incur significant sub-optimal commuting. Such job-housing imbalance has contributed to a so-called spatial mismatch problem. This study aims to visualise the excess commuting patterns of individual workers using the Integrated Data Infrastructure (IDI) from Statistics New Zealand. The visualisation suggests that over the last demi-decade, housing unaffordability has partially distorted the commuting patterns of key workers in Auckland. More of the working population, in particular those key workers, are displaced to the outer rings of the city. While there is an overall reduction in excess commuting across three groups of workers, key workers remain the working population with a disproportionate long excess commute.

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Methods for Inferring Route Choice of Commuting Trip From Mobile Phone Network Data

Cited by 16 publications

References 41 publications

A Novel Method to Determine the Optimal Location for a Cellular Tower by Using LiDAR Data

A Novel Method to Determine the Optimal Location for a Cellular Tower by Using LiDAR Data

Mobile Technology and Studies on Transport Behavior: A Literature Analysis, Integrated Research Model, and Future Research Agenda

Understanding the Spatial Effects of Unaffordable Housing Using the Commuting Patterns of Workers in the New Zealand Integrated Data Infrastructure

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