Development of a global positioning system data-based trip-purpose inference method for hazardous materials transportation management

2019 ◽  
Vol 24 (1) ◽  
pp. 24-39 ◽  
Author(s):  
Huiying Zhao ◽  
Dalin Qian ◽  
Ying Lv ◽  
Bo Zhang ◽  
Rongyu Liang
2013 ◽  
Vol 28 ◽  
pp. e2013005 ◽  
Author(s):  
Daikwon Han ◽  
Kiyoung Lee ◽  
Jongyun Kim ◽  
Deborah H. Bennett ◽  
Diana Cassady ◽  
...  

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1144-1158 ◽  
Author(s):  
Asif Nawaz ◽  
Huang Zhiqiu ◽  
Wang Senzhang ◽  
Yasir Hussain ◽  
Amara Naseer ◽  
...  

Many applications use the Global Positioning System data that provide rich context information for multiple purposes. Easier availability and access of Global Positioning System data can facilitate various mobile applications, and one of such applications is to infer the mobility of a user. Most existing works for inferring users’ transportation modes need the combination of Global Positioning System data and other types of data such as accelerometer and Global System for Mobile Communications. However, the dependency of the applications to use data sources other than the Global Positioning System makes the use of application difficult if peer data source is not available. In this paper, we introduce a new generic framework for the inference of transportation mode by only using the Global Positioning System data. Our contribution is threefold. First, we propose a new method for Global Positioning System trajectory data preprocessing using grid probability distribution function. Second, we introduce an algorithm for the change point–based trajectory segmentation, to more effectively identify the single-mode segments from Global Positioning System trajectories. Third, we introduce new statistical-based topographic features that are more discriminative for transportation mode detection. Through extensive evaluation on the large trajectory data GeoLife, our approach shows significant performance improvement in terms of accuracy over state-of-the-art baseline models.


2020 ◽  
Vol 14 (1) ◽  
pp. 113-118 ◽  
Author(s):  
Y. Facio ◽  
M. Berber

AbstractPost Processed Static (PPS) and Precise Point Positioning (PPP) techniques are not new; however, they have been refined over the decades. As such, today these techniques are offered online via GPS (Global Positioning System) data processing services. In this study, one Post Processed Static (OPUS) and one Precise Point Positioning (CSRS-PPP) technique is used to process 24 h GPS data for a CORS (Continuously Operating Reference Stations) station (P565) duration of year 2016. By analyzing the results sent by these two online services, subsidence is determined for the location of CORS station, P565, as 3–4 cm for the entire year of 2016. In addition, precision of these two techniques is determined as ∼2 cm. Accuracy of PPS and PPP results is 0.46 cm and 1.21 cm, respectively. Additionally, these two techniques are compared and variations between them is determined as 2.5 cm.


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