scholarly journals A Review of GPS Trajectories Classification Based on Transportation Mode

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3741 ◽  
Author(s):  
Xue Yang ◽  
Kathleen Stewart ◽  
Luliang Tang ◽  
Zhong Xie ◽  
Qingquan Li
Keyword(s):  
Data Acquisition ◽  
Mixed Mode ◽  
Moving Objects ◽  
Single Mode ◽  
Point Of View ◽  
Location Based Services ◽  
Gps Data ◽  
Transportation Mode ◽  
Gps Trajectories ◽  
Transition Points

GPS trajectories generated by moving objects provide researchers with an excellent resource for revealing patterns of human activities. Relevant research based on GPS trajectories includes the fields of location-based services, transportation science, and urban studies among others. Research relating to how to obtain GPS data (e.g., GPS data acquisition, GPS data processing) is receiving significant attention because of the availability of GPS data collecting platforms. One such problem is the GPS data classification based on transportation mode. The challenge of classifying trajectories by transportation mode has approached detecting different modes of movement through the application of several strategies. From a GPS data acquisition point of view, this paper macroscopically classifies the transportation mode of GPS data into single-mode and mixed-mode. That means GPS trajectories collected based on one type of transportation mode are regarded as single-mode data; otherwise it is considered as mixed-mode data. The one big difference of classification strategy between single-mode and mixed-mode GPS data is whether we need to recognize the transition points or activity episodes first. Based on this, we systematically review existing classification methods for single-mode and mixed-mode GPS data and introduce the contributions of these methods as well as discuss their unresolved issues to provide directions for future studies in this field. Based on this review and the transportation application at hand, researchers can select the most appropriate method and endeavor to improve them.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

Statistical characteristics and transportation mode identification of individual trajectories

2020 ◽  
Vol 34 (10) ◽  
pp. 2050092
Author(s):  
Zhiren Huang ◽  
Pu Wang ◽  
Yang Liu
Keyword(s):  
Human Mobility ◽  
Location Based Services ◽  
Statistical Characteristics ◽  
Trajectory Data ◽  
Single Class ◽  
Transportation Mode ◽  
Mode Identification ◽  
Transportation Modes ◽  
Gps Trajectory Data ◽  
Gps Trajectories

Entering big data era, individual GPS trajectory data have created great opportunities for human mobility and collective behavior studies. Individual GPS trajectories can be collected by location-based services on mobile phones. However, GPS data often do not record transportation modes (e.g., walking, riding a bus, or driving a car). In this study, we analyzed the statistical characteristics of individual trajectories and present a collaborative isolation forest (Co-IF) model to identify the transportation modes of mobile phone GPS trajectories. Unlike previous models that identify multiple transportation modes simultaneously, the proposed Co-IF model builds a single-class classifier for each transportation mode and then combines their results. Compared to the existing models, the Co-IF model offers competitive performance and shows improved reliability with noisy trajectories.

An Enhanced Transportation Mode Detection Method Based on GPS Data

2017 ◽  
pp. 605-620
Author(s):  
Jing Liang ◽  
Qiuhui Zhu ◽  
Min Zhu ◽  
Mingzhao Li ◽  
Xiaowei Li ◽  
...  
Keyword(s):  
Detection Method ◽  
Gps Data ◽  
Transportation Mode ◽  
Mode Detection

Multichannel FMCW lidar for imaging velocimetry and range finding

2021 ◽  
Author(s):  
Iskander Gazizov ◽  
Sergei Zenevich ◽  
Oleg Benderov ◽  
Alexander Rodin
Keyword(s):  
Near Infrared ◽  
Moving Objects ◽  
Single Channel ◽  
Basic Research ◽  
Single Mode ◽  
Single Mode Fiber ◽  
Time Data ◽  
Range Finding ◽  
Scan Time ◽  
Laser Control

<p>We present a concept of near-infrared FMCW lidar for real-time low-resolution imaging velocimetry and range finding of moving objects. One of the problems this instrument to challenge is the detection of unmanned aerial vehicles in an urban environment. The use of a lidar-based system is either in the detection of the object itself or of the wingtip vortices generated by rotating blades. A significant drawback of typical wind lidar is the long measurement time associated with the need to scan the area of ​​interest, therefore we propose an 8x2 matrix of receivers to reduce the total scan time. The main feature of the instrument is the use of commercially available components, including DFB lasers and single-mode fiber for the optical circuit, which can significantly reduce the cost of the device, as well as development time. Data processing and laser control are handled by the FPGA. The characteristics of the multichannel lidar are estimated based on ongoing testing of the single-channel prototype.</p><p><strong>Acknowledgements</strong></p><p>This work has been supported by the Russian Foundation for Basic Research grants #19-29-06104</p>

Database Queries in Mobile Environments

2011 ◽  
pp. 267-284
Author(s):  
N. Marsit
Keyword(s):  
Scientific Community ◽  
Moving Objects ◽  
Research Work ◽  
Location Based Services ◽  
Technological Evolution ◽  
Mobile Terminals ◽  
Database Queries ◽  
Positioning Systems ◽  
Work Related ◽  
Comprehensive Survey

The technological evolution of networks together with the development of positioning systems has contributed to the emergence of numerous location-based services. Services related to this expanding area will become of major technical as well as economical interest in the coming few years. This aroused a great deal of interest from the scientific community at large and specifically from those studying these services and their diverse requirements and constraints. One of the direct consequences in the database field is the appearance of new types of queries (mobile queries issued from mobile terminals and/or requesting information associated with moving objects such as vehicles). Our objective in this chapter is to present a comprehensive survey of the field of research work related to mobile queries, with particular attention to the location issue.

Ontologies for Location-Based Services

2011 ◽  
pp. 54-68
Author(s):  
Matthias Brantner ◽  
Sven Helmer ◽  
Carl-Christian Kanne ◽  
Guido Moerkotte
Keyword(s):  
Semantic Information ◽  
Point Of View ◽  
Location Based Services ◽  
Mobile Business ◽  
Technical Data ◽  
Practical Point ◽  
Business Application

A user of a mobile business application is usually not interested in technical data, but its meaning (which may also vary from user to user). We discuss how ontologies can help in translating this technical, location-based data (e.g. geographical coordinates) into semantic information. Taking a practical point of view, we first define typical requirements of location-based services, develop an ontology for locations, and show how this ontology can be integrated into existing technologies.

Diverse Models of Distance Teaching Universities

2011 ◽  
pp. 727-733 ◽  
Author(s):  
Sarah Guri-Rosenblit
Keyword(s):  
Continuing Education ◽  
Mixed Mode ◽  
Relevant Literature ◽  
Single Mode ◽  
Admission Policy ◽  
Distance Teaching ◽  
Organizational Models ◽  
Virtual Technology ◽  
Entry Requirements ◽  
Education Courses

Universities offering studies through distance teaching methods vary enormously in how they were initiated, the clienteles they aim to serve, how they are funded, and the kinds of programs they offer. Distance teaching at university level is provided currently through at least five major organizational models: Single-mode distance teaching universities; dual- and mixed-mode universities; extensions; consortia-type ventures; and virtual technology-based universities. Each of these models can be divided into additional sub-groups. The fully-fledged distance teaching universities, for instance, are treated in the relevant literature as a generic group, but differ from each other in many respects (Guri-Rosenblit, 1999). Some are operating as huge national universities, while others function on a limited provincial level. Few adopted an open admission policy, while most others require the same entry requirements as their conventional counterparts, etc. The dual- and the mixed-mode universities, as well as the consortia-type ventures, constitute nowadays the leading models of distance teaching provision. They operate in many national settings, and represent a rich composition of diverse higher education institutions, such as: research versus mainly teaching-oriented universities; large and small establishments; fully accredited or experimental in nature; offering mainly continuing education courses versus full academic degrees. However, this overview analyzes only the underlying premises of distance teaching in each of the five major models. Its scope does not allow discussing in detail the sub-groups contained in each model.

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