Trajectory Data Acquisition via Private Car Positioning Based on Tightly-coupled GPS/OBD Integration in Urban Environments

Xiao, Zhu; Chen, Yanxun; Alazab, Mamoun; Chen, Hongyang

doi:10.1109/tits.2021.3105550

Cited by 18 publications

(2 citation statements)

References 43 publications

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“…The research data were obtained using low-cost GNSS-OBD devices in real-world working scenarios. The data collection period was from 12:00 a.m. to 11:59 p.m. on 1 July 2018, with a sampling frequency of 1 Hz, a time resolution of 0.01 s, and a position resolution of 0.1 m. The average positional error could be controlled within 10 m [63,64]. The data mainly include vehicle information ID, trip start time, trip end time, start point latitude and longitude (unit: degree), end point latitude and longitude (unit: degree), driving distance (unit: meter), travel time (unit: second), and fuel consumption (unit: milliliter), as shown in Table 1 [65].…”

Section: Data Sourcesmentioning

confidence: 99%

Impact of Built Environment on Carbon Emissions from Cross-District Mobility: A Social Network Analysis Based on Private Vehicle Trajectory Big Data

Chen

Xiao

2023

Sustainability

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The realization of the “double carbon” goals and the development of green transportation require a focused approach to reducing carbon emissions from private cars. Starting from the perspective of social network analysis, this paper constructs the carbon emission network of private car cross-district mobility based on vehicle trajectory big data in Guangzhou and Foshan and analyzes its spatial network characteristics. Next, the MRQAP model is constructed to examine the impact of built environment factors on carbon emissions from private cars. Furthermore, the paper explores the moderating effect of private car mobility in the central urban area. The results indicate the following: (1) Private vehicle cross-district mobility in the Guangzhou and Foshan region are closely interconnected and exhibit a phenomenon of central clustering. (2) Both population density and the number of road intersections have a positive relationship with private car carbon emissions, and after a series of robustness tests, the results are still valid. (3) Private vehicle mobility in central urban areas contributes to an increase in carbon emissions, and the positive impact is reinforced by population density, while road intersections and private car mobility in central urban areas have a substitutive effect on private car carbon emissions.

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Section: Data Sourcesmentioning

confidence: 99%

Impact of Built Environment on Carbon Emissions from Cross-District Mobility: A Social Network Analysis Based on Private Vehicle Trajectory Big Data

Chen

Xiao

2023

Sustainability

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“…The age of artificial intelligence technologies and information explosion has triggered the growth of machine learning in which machines are trained with known data ( Long et al, 2023 ; Huang et al, 2021 ) and then are used to predict future outcomes ( Gandomi, Chen & Abualigah, 2022 ; Xiao et al, 2023 ; Liu et al, 2020 ). Machine learning is essential in the field of data science.…”

Section: Introductionmentioning

confidence: 99%

A transformer-based deep learning framework to predict employee attrition

2023

PeerJ Computer Science

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In all areas of business, employee attrition has a detrimental impact on the accuracy of profit management. With modern advanced computing technology, it is possible to construct a model for predicting employee attrition to minimize business owners’ costs. Despite the reality that these types of models have never been evaluated under real-world conditions, several implementations were developed and applied to the IBM HR Employee Attrition dataset to evaluate how these models may be incorporated into a decision support system and their effect on strategic decisions. In this study, a Transformer-based neural network was implemented and was characterized by contextual embeddings adapting to tubular data as a computational technique for determining employee turnover. Experimental outcomes showed that this model had significantly improved prediction efficiency compared to other state-of-the-art models. In addition, this study pointed out that deep learning, in general, and Transformer-based networks, in particular, are promising for dealing with tabular and unbalanced data.

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Green Transition Driven Carbon Trading Mechanism and Design Based on Urban Vehicle Trajectory Data

Chen,

Wu,

Xiao

2022

Edge Computing and IoT: Systems, Management and Security

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Trajectory Data Acquisition via Private Car Positioning Based on Tightly-coupled GPS/OBD Integration in Urban Environments

Cited by 18 publications

References 43 publications

Impact of Built Environment on Carbon Emissions from Cross-District Mobility: A Social Network Analysis Based on Private Vehicle Trajectory Big Data

Impact of Built Environment on Carbon Emissions from Cross-District Mobility: A Social Network Analysis Based on Private Vehicle Trajectory Big Data

A transformer-based deep learning framework to predict employee attrition

Green Transition Driven Carbon Trading Mechanism and Design Based on Urban Vehicle Trajectory Data

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