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Probabilistic Multimodal Map Matching With Rich Smartphone Data
2014
Journal of Intelligent Transportation Systems / Taylor & Francis
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There are also studies on detecting transport modes from GPS data. A recent study on probabilistic map matching shows that knowing the transport modes helps in identifying the true paths. ...
The model doesn't require pre-processing of raw data into segments with single transport modes. The problem is modeled in a probabilistic manner such that error in measurements can be accounted for. ...
The identification of mode and path from GPS data has drawn a lot of attentions in transport research (e.g., Schuessler and Axhausen, 2009a,b; Liao et al., 2007a) . ...
doi:10.1080/15472450.2013.764796
fatcat:asyqg6qxnnguvjuqmsdl7pip4a
Trip mode inference from mobile phone signaling data using Logarithm Gaussian Mixture Model
2020
Journal of Transport and Land Use
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This study provides an important opportunity to infer trip mode from the aspect of probability using mobile phone signaling data. ...
Trip mode inference plays an important role in transportation planning and management. Most studies in the field have focused on the methods based on GPS data collected from mobile devices. ...
Data set Data set used in this study consists of mobile phone signaling data and cell phone tower data in Shanghai for the period from May 4th to May 17th of 2015. ...
doi:10.5198/jtlu.2020.1554
fatcat:lohoi5o6n5gjzgrr2c6dy3b3lq
A Strategy on How to Utilize Smartphones for Automatically Reconstructing Trips in Travel Surveys
2012
Procedia - Social and Behavioral Sciences
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In the region of Vienna, Austria, 266 hours of travel data were collected to train and evaluate the models. ...
Railway modes were correctly identified in 80% of all cases, which is subject to further research. In case of GPS losses only accelerometer data are used, which still shows promising results. ...
Acknowledgements This work was carried out in the scope of the Austrian research project NEMO-PHONE (Novel Methods for Collecting Mobility Data with Smartphones), which is funded by the Austrian Federal ...
doi:10.1016/j.sbspro.2012.06.1080
fatcat:h57aiu7yprf6dk5fcjhxlez63u
Transport mode detection based on mobile phone network data: A systematic review
2019
Transportation Research Part C: Emerging Technologies
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This paper provides an in-depth, systematic review of transport mode detection based on mobile phone network data. ...
This paper provides an in-depth, systematic review of transport mode detection based on mobile phone network data. ...
They detected transport modes from CDR data using an RBH method that combines trip speed, trip distance, proximity to public transport network, and a logit model. ...
doi:10.1016/j.trc.2019.02.008
fatcat:hlmjnl7imjbj5hkjyu4vchbdja
Emerging Big Data Sources for Public Transport Planning: A Systematic Review on Current State of Art and Future Research Directions
2019
Journal of the Indian Institute of Science
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Huang et al. 34 reviewed the advantages and disadvantages of different methods to detect transport mode based on mobile phone network data. ...
(b) Mobile phone data At present, most individuals carry mobile phone almost everywhere, which results in mobile phone datathe largest human mobility data source 8 . ...
doi:10.1007/s41745-019-00125-9
fatcat:5qm66wzthzejdg67ed6uumbh2a
Effector: Energy Efficient Mobility Classification and State Based Route Creation
2016
International Journal of Science and Research (IJSR)
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mobile phones. ...
On demand remote data exchange for analysis and processing of measurements plays a key role in mobility state analysis using accelerometer sensor which is less energy efficient has higher network costs ...
Using mobile phones to determine transportation modes [9] focuses on transportation mode of an individual when outside, whether the user is stationary, walking, running, biking or in motorized transport ...
doi:10.21275/v5i4.nov162789
fatcat:tbvg7p2qtbabdga2rvm3m7o55q
Shaka: User Movement Estimation Considering Reliability, Power Saving, and Latency Using Mobile Phone
2011
IEICE transactions on information and systems
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This paper proposes a method for using an accelerometer, microphone, and GPS in a mobile phone to recognize the movement of the user. ...
Shaka's power saving functionality enables us to extend the battery life of a mobile phone to over 100 hours while our estimation algorithm is running in the background. ...
Acknowledgments The author would like to thank his partner researcher Yoshihiro Kawahara at the University of Tokyo for collecting huge volumes of experimental data. ...
doi:10.1587/transinf.e94.d.1153
fatcat:ebbkm6q7czbxtoj7tezabts7dm
TRACKING VEHICLE IN GSM NETWORK TO SUPPORT INTELLIGENT TRANSPORTATION SYSTEMS
2012
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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To exploit the potential of turning these mobile devices into dynamic data acquisition nodes that provides valuable data for Intelligent Transportation Systems (ITS), position information is needed. ...
Both the potential commercial applications and the use of the derived position data in ITS is discussed for tracking vehicles and monitoring traffic flow. ...
Most of these devices use GSM network, therefore mass location data can be extracted from GSM network side. This information can be used to understand the human mobility patterns. ...
doi:10.5194/isprsarchives-xxxix-b2-139-2012
fatcat:vty4ep33yveqfkb2rotjfgideu
Exploitation of Aggregate Mobility Sensing Data for the Synthesis of Disaggregate Multimodal Tours in Megacities
2021
Frontiers in Future Transportation
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Implications are significant since the creation of such granular mobility information from widely available data sources like aggregate ODs can prove particularly useful for deep explanatory analysis or ...
for advanced transport modeling purposes (e.g., agent-based, microsimulation modeling). ...
This attribute holds particularly true for ODs deriving from urban sensing data sources (e.g., mobile phone data, GPS, etc.) since they are built by continuously tracking the movements of mobile phone ...
doi:10.3389/ffutr.2021.647852
fatcat:juti32uohfaypjpqeunlrbskoq
Passenger BIBO detection with IoT support and machine learning techniques for intelligent transport systems
2020
Procedia Computer Science
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The present article discusses the issue of automation of the CICO (Check-In/Check-Out) process for public transport fare collection systems, using modern tools forming part of the Internet of Things, such ...
It describes the concept of an integrated passenger identification model applying machine learning technology in order to reduce or eliminate the risks associated with the incorrect classification of a ...
This mode enables the collection and analysis of comprehensive data and relationships of the integrated passenger identification model. ...
doi:10.1016/j.procs.2020.09.009
fatcat:psfi5jutcja3pg6qtlkuandg6m
Crowd Intelligence for Sustainable Futuristic Intelligent Transportation System: A Review
2020
IET Intelligent Transport Systems
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Crowd intelligence is a combined method of data collection, integration and analysis from devices such as the smartphones, wearables, vehicles and a wide range of Internet of Things applications to use ...
From this survey, various challenges of the intelligent transportation system have been outlined and crowd-intelligent solutions have been discussed. ...
Another approach of mobility pattern modelling uses the GPS data and extracts mobility models from the data by using geometric and probabilistic models [243] . Hafezi et al. ...
doi:10.1049/iet-its.2019.0321
fatcat:2krdzlefdndbxfx3uhlzexhps4
Deriving Personal Trip Data from GPS Data: A Literature Review on the Existing Methodologies
2014
Procedia - Social and Behavioral Sciences
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In addition, the GPS data error identification and the trip segment from the continuous GPS data are quite fundamental to transportation mode identification and trip purpose inference. ...
Although GPS data could provide precise spatiotemporal information of vehicular or personal movements, the transportation mode (in the case of personal movements with wearable GPS devices) and trip purpose ...
It means that GPS data with higher accuracy can be obtained with smart mobile phones. ...
doi:10.1016/j.sbspro.2014.07.239
fatcat:jw3s57om7rak7a44b6lswmmrca
Recent Progress in Activity-Based Travel Demand Modeling: Rising Data and Applicability
[chapter]
2020
Transportation Systems for Smart, Sustainable, Inclusive and Secure Cities [Working Title]
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Activity-based models are valuable tools for transportation planning and analysis, detailing the tour and mode-restricted nature of the household and individual travel choices. ...
The big data enables new ABM models to reflect mobility behavior on an unprecedented level of detail while collecting data over a longer period (e.g., more than one typical day) would improve the behavioral ...
Benitez, Deriving origin-destination data from a mobile phone network. ...
doi:10.5772/intechopen.93827
fatcat:7a7ygjcwgbh5he53dyd7gtelfu
Identifying latent shared mobility preference segments in low-income communities: ride-hailing, fixed-route bus, and mobility-on-demand transit
[article]
2021
arXiv
pre-print
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People from the shared-mode enthusiast segment often use ride-hailing services and live in areas with poor transit access, and they are likely to be the early adopters of MOD transit services. ...
Concepts of Mobility-on-Demand (MOD) and Mobility as a Service (MaaS), which feature the integration of various shared-use mobility options, have gained widespread popularity in recent years. ...
STUDY AREA AND DATA PROCESSING This study uses survey data from residents who live in low-income neighborhoods, focusing on their shared mobility preferences and usage. ...
arXiv:2107.04412v1
fatcat:bh5s3oe47fhshnkv6cr24h4rqm
Social Network Friend Recommendation System Using Semantic Web
2016
International Journal of Science and Research (IJSR)
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Using text mining, daily activities of users are modelled as a life documents. This life document is used for extracting user's life styles or habits by using Latent Dirichlet Allocation algorithm. ...
In this paper, a personalised friendbook recommendation mobile application is presented, which is a novel semantic based friend recommendation system for social networking services. ...
In probabilistic mining of sociographic routines from mobile phone data, Ferrahi and Gatica-Perez used approach of combined location and physical proximity captured by mobile phones to overcome problem ...
doi:10.21275/v5i1.nov152976
fatcat:fdjpn7tkpvfkjl7ifuadyp57ce
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